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.

Clinical role of abbreviated and ultrafast MRI in breast imaging

Current breast cancer screening relies on mammography, digital breast tomosynthesis and breast ultrasound. In select populations, breast MRI is also of great utility. However, multiple factors limit widespread use of breast MRI for screening. Efforts have been made to increase the availability of breast MRI for screening, in large part due to the increased cancer detection rate of breast MRI compared to mammography. Techniques include shortening standard breast MRI protocols with the potential for accommodating MRI screening in a higher number of patients. This review will explain the role of abbreviated breast MRI and ultrafast breast MRI in breast imaging, and detail how these approaches differ from standard dynamic contrast-enhanced breast MRI. In addition, limitations and advantages of these techniques will also be discussed.

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.

Auditing Abbreviated Breast MR Imaging: Clinical Considerations and Implications

Abbreviated breast MR (AB-MR) imaging is a relatively new breast imaging tool, which maintains diagnostic accuracy while reducing image times compared with full-protocol breast MR (FP-MR) imaging. Breast imaging audits involve calculating individual and organizational metrics, which can be compared with established benchmarks, providing a standard against which performance can be measured. Unlike FP-MR imaging, there are no established benchmarks for AB-MR imaging but studies demonstrate comparable performance for cancer detection rate, positive predictive value 3, sensitivity, and specificity with T2. We review the basics of performing an audit, including strategies to implement if benchmarks are not being met.

Optimized, Person-Centered Workflow Design for a High-Throughput Breast MRI Screening Facility-A Simulation Study

OBJECTIVES

This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized.

MATERIALS AND METHODS

A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables.

RESULTS

The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario.

CONCLUSIONS

This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.

Abbreviated breast magnetic resonance imaging (MRI) or digital breast tomosynthesis for breast cancer detection in dense breasts? A retrospective preliminary study with comparable results

AIM

To compare the diagnostic performance of abbreviated breast magnetic resonance (AB-MR) imaging (MRI) and digital breast tomosynthesis (DBT) for breast cancer detection in Malaysian women with dense breasts, using histopathology as the reference standard.

MATERIALS AND METHODS

This was a single-centre cross-sectional study of 115 women with American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BIRADS) breast density C and D on DBT with breast lesions who underwent AB-MR from June 2018 to December 2021. AB-MR was performed on a 3 T MRI system with an imaging protocol consisting of three sequences: axial T1 fat-saturated unenhanced; axial first contrast-enhanced; and subtracted first contrast-enhanced with maximum intensity projection (MIP). DBT and AB-MR images were evaluated by two radiologists blinded to the histopathology and patient outcomes. Diagnostic accuracy (sensitivity, specificity, positive predictive value [PPV] and negative predictive value [NPV]) was assessed.

RESULT

Of the 115 women, the mean age was 50.6 years. There were 48 (41.7%) Malay, 54 (47%) Chinese, and 12 (10.4%) Indian women. The majority (n=87, 75.7%) were from the diagnostic population. Sixty-one (53.1%) were premenopausal and 54 (46.9%) postmenopausal. Seventy-eight (72.4%) had an increased risk of developing breast cancer. Ninety-one (79.1%) women had density C and 24 (20.9%) had density D. There were 164 histopathology-proven lesions; 69 (42.1%) were malignant and 95 (57.9%) were benign. There were 62.8% (n=103/164) lesions detected at DBT. All the malignant lesions 100% (n=69) and 35.7% (n=34) of benign lesions were detected. Of the 61 lesions that were not detected, 46 (75.4%) were in density C, and 15 (24.6%) were in density D. The sensitivity, specificity, PPV, and NPV for DBT were 98.5%, 34.6%, 66.3%, and 94.7%, respectively. There were 65.2% (n=107/164) lesions detected on AB-MR, with 98.6% (n=68) malignant and 41.1% (39) benign lesions detected. The sensitivity, specificity, PPV, and NPV for AB-MR were 98.5%, 43.9%, 67.2%, and 96.2%, respectively. One malignant lesion (0.6%), which was a low-grade ductal carcinoma in-situ (DCIS), was missed on AB-MR.

CONCLUSION

The present findings suggest that both DBT and AB-MR have comparable effectiveness as an imaging method for detecting breast cancer and have high NPV for low-risk lesions in women with dense breasts.

Ultrafast MR imaging findings of 2 different subtypes in a male patient with bilateral breast cancer

Bilateral breast cancer in males is an exceedingly rare diagnosis. In this case report, we will discuss the ultrafast sequence findings of a bilateral male breast cancer with different subtypes on his staging dynamic contrast enhanced (DCE) MRI with ultrafast technique. A 94-year-old male presented with bilateral palpable complaints in his breasts. Diagnostic mammography and ultrasound images demonstrated bilateral irregular masses with nipple retraction. Biopsies were performed and the histopathologic examination revealed invasive breast carcinoma of no special type in 1 breast and invasive micropapillary carcinoma in the other breast. Staging MRI with ultrafast sequence showed significant enhancement differences between 2 different subtypes, correlating with the different levels of tumor aggressiveness. Different ultrafast metrics, such as time-to-enhancement and maximum slope, may help to differentiate between several subtypes of breast cancer and serve as prognostic indicators. This case report discusses the application of ultrafast sequence in predicting breast cancer subtypes in a male patient with bilateral disease.

Abbreviated Breast MRI: State of the Art

Abbreviated MRI is an umbrella term, defined as a focused MRI examination tailored to answer a single specific clinical question. For abbreviated breast MRI, this question is: "Is there evidence of breast cancer?" Abbreviated MRI of the breast makes maximum use of the fact that the kinetics of breast cancers and of benign tissue differ most in the very early postcontrast phase; therefore, abbreviated breast MRI focuses on this period. The different published approaches to abbreviated MRI include the following three subtypes: (a) short protocols, consisting of a precontrast and either a single postcontrast acquisition (first postcontrast subtracted [FAST]) or a time-resolved series of postcontrast acquisitions with lower spatial resolution (ultrafast [UF]), obtained during the early postcontrast phase immediately after contrast agent injection; (b) abridged protocols, consisting of FAST or UF acquisitions plus selected additional pulse sequences; and (c) noncontrast protocols, where diffusion-weighted imaging replaces the contrast information. Abbreviated MRI was proposed to increase tolerability of and access to breast MRI as a screening tool. But its widening application now includes follow-up after breast cancer and even diagnostic assessment. This review defines the three subtypes of abbreviated MRI, highlighting the differences between the protocols and their clinical implications and summarizing the respective evidence on diagnostic accuracy and clinical utility.

Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks

OBJECTIVES

To develop a deep learning-based method for contrast-enhanced breast lesion detection in ultrafast screening MRI.

MATERIALS AND METHODS

A total of 837 breast MRI exams of 488 consecutive patients were included. Lesion's location was independently annotated in the maximum intensity projection (MIP) image of the last time-resolved angiography with stochastic trajectories (TWIST) sequence for each individual breast, resulting in 265 lesions (190 benign, 75 malignant) in 163 breasts (133 women). YOLOv5 models were fine-tuned using training sets containing the same number of MIP images with and without lesions. A long short-term memory (LSTM) network was employed to help reduce false positive predictions. The integrated system was then evaluated on test sets containing enriched uninvolved breasts during cross-validation to mimic the performance in a screening scenario.

RESULTS

In five-fold cross-validation, the YOLOv5x model showed a sensitivity of 0.95, 0.97, 0.98, and 0.99, with 0.125, 0.25, 0.5, and 1 false positive per breast, respectively. The LSTM network reduced 15.5% of the false positive prediction from the YOLO model, and the positive predictive value was increased from 0.22 to 0.25.

CONCLUSIONS

A fine-tuned YOLOv5x model can detect breast lesions on ultrafast MRI with high sensitivity in a screening population, and the output of the model could be further refined by an LSTM network to reduce the amount of false positive predictions.

CLINICAL RELEVANCE STATEMENT

The proposed integrated system would make the ultrafast MRI screening process more effective by assisting radiologists in prioritizing suspicious examinations and supporting the diagnostic workup.

KEY POINTS

• Deep convolutional neural networks could be utilized to automatically pinpoint breast lesions in screening MRI with high sensitivity. • False positive predictions significantly increased when the detection models were tested on highly unbalanced test sets with more normal scans. • Dynamic enhancement patterns of breast lesions during contrast inflow learned by the long short-term memory networks helped to reduce false positive predictions.

Contrast-enhanced breast imaging: Current status and future challenges

BACKGROUND

Contrast-enhanced breast MRI and recently also contrast-enhanced mammography (CEM) are available for breast imaging. The aim of the current overview is to explore existing evidence and ongoing challenges of contrast-enhanced breast imaging.

METHODS

This narrative provides an introduction to the contrast-enhanced breast imaging modalities breast MRI and CEM. Underlying principle, techniques and BI-RADS reporting of both techniques are described and compared, and the following indications and ongoing challenges are discussed: problem-solving, high-risk screening, supplemental screening in women with extremely dense breast tissue, breast implants, neoadjuvant systemic therapy (NST) response monitoring, MRI-guided and CEM- guided biopsy.

RESULTS

Technique and reporting for breast MRI are standardised, for the newer CEM standardisation is in progress. Similarly, compared to other modalities, breast MRI is well established as superior for problem-solving, screening women at high risk, screening women with extremely dense breast tissue or with implants; and for monitoring response to NST. Furthermore, MRI-guided biopsy is a reliable technique with low long-term false negative rates. For CEM, data is as yet either absent or limited, but existing results in these settings are promising.

CONCLUSION

Contrast-enhanced breast imaging achieves highest diagnostic performance and should be considered essential. Of the two contrast-enhanced modalities, evidence of breast MRI superiority is ample, and preliminary results on CEM are promising, yet CEM warrants further study.

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.

Discrimination of benign and malignant breast lesions on dynamic contrast-enhanced magnetic resonance imaging using deep learning

PURPOSE

To evaluate the capability of deep transfer learning (DTL) and fine-tuning methods in differentiating malignant from benign lesions in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

METHODS

The diagnostic efficiencies of the VGG19, ResNet50, and DenseNet201 models were tested under the same dataset. The model with the highest performance was selected and modified utilizing three fine-tuning strategies (S1-3). Fifty additional lesions were selected to form the validation set to verify the generalization abilities of these models. The accuracy (Ac) of the different models in the training and test sets, as well as the precision (Pr), recall rate (Rc), F1 score (), and area under the receiver operating characteristic curve (AUC), were primary performance indicators. Finally, the kappa test was used to compare the degree of agreement between the DTL models and pathological diagnosis in differentiating malignant from benign breast lesions.

RESULTS

The Pr, Rc, f1, and AUC of VGG19 (86.0%, 0.81, 0.81, and 0.81, respectively) were higher than those of DenseNet201 (70.0%, 0.61, 0.63, and 0.61, respectively) and ResNet50 (61.0%, 0.59, 0.59, and 0.59). After fine-tuning, the Pr, Rc, f1, and AUC of S1 (87.0%, 0.86, 0.86, and 0.86, respectively) were higher than those of VGG19. Notably, the degree of agreement between S1 and pathological diagnosis in differentiating malignant from benign breast lesions was 0.720 (κ = 0.720), which was higher than that of DenseNet201 (κ = 0.440), VGG19 (κ = 0.640), and ResNet50 (κ = 0.280).

CONCLUSION

The VGG19 model is an effective method for identifying benign and malignant breast lesions on DCE-MRI, and its performance can be further improved via fine-tuning. Overall, our findings insinuate that this technique holds potential clinical application value.

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.

New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening

Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.

Comparison of Fused Diffusion-Weighted Imaging Using Unenhanced MRI and Abbreviated Post-Contrast-Enhanced MRI in Patients with Breast Cancer

Background and Objectives: To determine the percentage of breast cancers detectable by fused diffusion-weighted imaging (DWI) using unenhanced magnetic resonance imaging (MRI) and abbreviated post-contrast-enhanced MRI. Materials and Methods: Between October 2016 and October 2017, 194 consecutive women (mean age, 54.2 years; age range, 28-82 years) with newly diagnosed unilateral breast cancer, who underwent preoperative 3.0 T breast MRI with DWI, were evaluated. Both fused DWI and abbreviated MRI were independently reviewed by two radiologists for the detection of index cancer (which showed the most suspicious findings in both breasts), location, lesion conspicuity, lesion type, and lesion size. Moreover, the relationship between cancer detection and histopathological results of surgical specimens was evaluated. Results: Index cancer detection rates were comparable between fused DWI and abbreviated MRI (radiologist 1: 174/194 [89.7%] vs. 184/194 [94.8%], respectively, p = 0.057; radiologist 2: 174/194 [89.7%] vs. 183/194 [94.3%], respectively, p = 0.092). In both radiologists, abbreviated MRI showed a significantly higher lesion conspicuity than fused DWI (radiologist 1: 9.37 ± 2.24 vs. 8.78 ± 3.03, respectively, p < 0.001; radiologist 2: 9.16 ± 2.32 vs. 8.39 ± 2.93, respectively, p < 0.001). The κ value for the interobserver agreement of index cancer detection was 0.67 on fused DWI and 0.85 on abbreviated MRI. For lesion conspicuity, the intraclass correlation coefficients were 0.72 on fused DWI and 0.82 on abbreviated MRI. Among the histopathological factors, tumor invasiveness was associated with cancer detection on both fused DWI (p = 0.011) and abbreviated MRI (p = 0.004, radiologist 1), lymphovascular invasion on abbreviated MRI (p = 0.032, radiologist 1), and necrosis on fused DWI (p = 0.031, radiologist 2). Conclusions: Index cancer detection was comparable between fused DWI and abbreviated MRI, although abbreviated MRI showed a significantly better lesion conspicuity.

The efficacy of abbreviated breast MRI protocols using 1.5 T MRI in the preoperative staging of newly diagnosed breast cancers

PURPOSE

To determine the efficacy of abbreviated breast magnetic resonance imaging (MRI) protocols using 1.5 T MRI in the preoperative staging of newly diagnosed breast cancers.

METHODS

Eighty patients who underwent 1.5 T MRI between August 2014 and January 2018 for the preoperative staging of breast cancer were evaluated retrospectively. Three separate abbreviated breast MRI protocols (AP) were created from a full protocol, and the images were evaluated independently by two radiologists. AP1 included axial fat-saturated T2 weighted and diffusion-weighted (DW) images, while subtracted axial fat-saturated T1 weighted images were obtained 2 min after contrast administration in AP2. Finally, AP2 and DW images were evaluated in AP3. Lesion location, number, and size, and presence of axillary lymphadenopathy were evaluated in each protocol. Pathological data (lesion quadrant, lesion size, and presence of axillary metastases) from the 80 patients were compared with the abbreviated protocols and full diagnostic protocol.

RESULTS

The best correlation with the full protocol for detecting the lesion quadrant, number of lesions, and presence of axillary lymphadenopathy was achieved with AP3 for both readers (κ = 0.954, 0.954 for the lesion quadrant, κ = 0.971, 0.910 for the number of lesions, and κ = 0.973, 0.865 for the axillary lymphadenopathy). The evaluation time in all abbreviated protocols was shorter than for the full protocol (p < 0.05). Comparing the abbreviated protocols with pathological data for both readers, the best correlation for detecting the lesion quadrant, number of lesions, and presence of axillary lymphadenopathy was achieved with AP3 (κ = 0.939, 0.954 for the lesion quadrant, κ = 0.941, 0.879 for the number of lesions, and κ = 0.842, 0.740 for axillary lymphadenopathy, respectively).

CONCLUSION

Abbreviated breast MRI protocols can provide sufficient diagnostic accuracy in the preoperative staging of breast cancer, with shorter imaging and evaluation times.

Implementation of abbreviated breast MRI in diagnostic and screening settings

BACKGROUND

Abbreviated magnetic resonance imaging (MRI) includes fewer sequences than standard MRI, which could be utilized for breast cancer detection.

PURPOSE

To evaluate the diagnostic accuracy of abbreviated MRI protocol in screening and diagnostic settings.

MATERIAL AND METHODS

All women with screening and diagnostic (problem-solving and preoperative staging) MRI examination were recruited from 2017 to 2020. Two expert radiologists assessed designed abbreviated protocol (fat-saturated T1-weighted [T1W] pre-contrast and two first fat-saturated T1W post-contrast series with reconstruction of their subtraction) including maximum intensity projection (MIP) and then evaluated standard protocol of breast MRI. Associated findings, including axillary lymphadenopathy and invasion to nipple, skin, or pectoralis muscle were also evaluated. The concordance rate of abbreviated with standard protocol in screening and diagnostic settings were also compared, based on BI-RADS classification. Diagnostic accuracy, sensitivity, specificity, and positive and negative predictive value were calculated.

RESULTS

A total of 108 (26.5%) of 408 patients (mean age = 43 ± 9 years) were classified as BI-RADS 4-5 and considered positive findings based on suspicious enhancement (mass or non-mass enhancement). Compared to standard protocol, abbreviated protocol revealed >98% accuracy in the diagnostic setting as well as 100% accuracy in the screening setting. Concordance rates in screening and diagnostic settings were 99.6% and 98.1%, respectively. There was no discordance between abbreviated and standard protocol in the evaluation of associated findings.

CONCLUSION

Abbreviated MRI protocol possesses substantial diagnostic accuracy in both screening and diagnostic settings. Additional information provided by standard protocol might not require for cancer detection.

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.

Abbreviated Molecular Breast Imaging: Feasibility and Future Considerations

OBJECTIVE

Molecular breast imaging (MBI) is a supplemental screening modality consistently demonstrating incremental cancer detection over mammography alone; however, its lengthy duration may limit widespread utilization. The study purpose was to assess feasibility of an abbreviated MBI protocol, providing readers with mediolateral oblique (MLO) projections only and assessing performance in lesion detection and localization.

METHODS

Retrospective IRB-exempt blinded reader study administered to 5 fellowship-trained breast imaging radiologists. Independent reads performed for 124 screening MBI cases, half abnormal and half negative/normal. Readers determined whether an abnormality was present, side of abnormality, and location of abnormality (medial/lateral). Abnormal cases had confirmatory biopsy or surgical pathology; normal cases had imaging follow-up ensuring true negative results. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess performance. A false negative result indicated that a reader failed to detect abnormal uptake; a false positive result indicated a reader incorrectly called an abnormality for a negative case. Tests for association included chi-square, Fisher-exact, and analysis of variance.

RESULTS

Mean reader performance for detecting abnormal uptake: sensitivity 96.8%, specificity 98.7%, PPV 98.8%, and NPV 96.9%. Accuracy in localizing lesions to the medial or lateral breast was 100%. There were no associations in reader performance with reader experience, reader technique, lesion morphology, or lesion pathology. Median lesion size was 1.0 cm (range: 0.4-8.0 cm). All readers correctly identified 97.7% (42/43) of lesions with malignant or elevated risk pathology.

CONCLUSION

An abbreviated MBI protocol (MLO images only) maintained high accuracy in lesion detection and localization.

Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer Screening

Breast cancer screening has evolved substantially over the past few decades because of advancements in new image acquisition systems and novel artificial intelligence (AI) algorithms. This review provides a brief overview of the history, current state, and future of AI in breast cancer screening and diagnosis along with challenges involved in the development of AI systems. Although AI has been developing for interpretation tasks associated with breast cancer screening for decades, its potential to combat the subjective nature and improve the efficiency of human image interpretation is always expanding. The rapid advancement of computational power and deep learning has increased greatly in AI research, with promising performance in detection and classification tasks across imaging modalities. Most AI systems, based on human-engineered or deep learning methods, serve as concurrent or secondary readers, that is, as aids to radiologists for a specific, well-defined task. In the future, AI may be able to perform multiple integrated tasks, making decisions at the level of or surpassing the ability of humans. Artificial intelligence may also serve as a partial primary reader to streamline ancillary tasks, triaging cases or ruling out obvious normal cases. However, before AI is used as an independent, autonomous reader, various challenges need to be addressed, including explainability and interpretability, in addition to repeatability and generalizability, to ensure that AI will provide a significant clinical benefit to breast cancer screening across all populations.

Beyond N Staging in Breast Cancer: Importance of MRI and Ultrasound-based Imaging

The correct N-staging in breast cancer is crucial to tailor treatment and stratify the prognosis. N-staging is based on the number and the localization of suspicious regional nodes on physical examination and/or imaging. Since clinical examination of the axillary cavity is associated with a high false negative rate, imaging modalities play a central role. In the presence of a T1 or T2 tumor and 0–2 suspicious nodes, on imaging at the axillary level I or II, a patient should undergo sentinel lymph node biopsy (SLNB), whereas in the presence of three or more suspicious nodes at the axillary level I or II confirmed by biopsy, they should undergo axillary lymph node dissection (ALND) or neoadjuvant chemotherapy according to a multidisciplinary approach, as well as in the case of internal mammary, supraclavicular, or level III axillary involved lymph nodes. In this scenario, radiological assessment of lymph nodes at the time of diagnosis must be accurate. False positives may preclude a sentinel lymph node in an otherwise eligible woman; in contrast, false negatives may lead to an unnecessary SLNB and the need for a second surgical procedure. In this review, we aim to describe the anatomy of the axilla and breast regional lymph node, and their diagnostic features to discriminate between normal and pathological nodes at Ultrasound (US) and Magnetic Resonance Imaging (MRI). Moreover, the technical aspects, the advantage and limitations of MRI versus US, and the possible future perspectives are also analyzed, through the analysis of the recent literature.

Prospective Evaluation of Ultrafast Breast MRI for Predicting Pathologic Response after Neoadjuvant Therapies

Background Ultrafast dynamic contrast-enhanced (DCE) MRI parameters are associated with breast cancer aggressiveness. However, the role of these parameters as predictive biomarkers for pathologic response after neoadjuvant chemotherapy (NAC) has been poorly investigated. Purpose To assess whether semiquantitative perfusion parameters calculated at initial ultrafast DCE MRI are associated with early prediction for pathologic response after NAC in participants with breast cancer. Materials and Methods This prospective single-center study included consecutive women with nonmetastatic invasive breast cancer treated with NAC followed by surgery who underwent initial ultrafast DCE MRI between December 2020 and August 2021. Six semiquantitative ultrafast DCE MRI parameters were calculated for each participant from the fitted time-signal intensity curve. Multivariable logistic regression was used to identify independent predictors of pathologic complete response (pCR) and residual cancer burden (RCB). Results Fifty women (mean age, 49 years ± 12 [SD]) were included in the study; 20 achieved pCR and 25 achieved low RCB (RCB-0 and I). A wash-in slope (WIS) cutoff value of 1.6% per second had a sensitivity of 94% (17 of 18 participants) and a specificity of 59% (19 of 32 participants) for pCR. A WIS of more than 1.6% per second (odds ratio [OR], 8.4 [95% CI: 1.5, 48.2]; P = .02), human epidermal growth factor receptor 2 (HER2) positivity (OR, 6.3 [95% CI: 1.5, 27.4]; P = .01), and tumor-infiltrating lymphocytes of more than 10% (OR, 6.9 [95% CI: 1.3, 37.7]; P = .03) were independent predictive factors of pCR. The area under the receiver operating characteristic curve of the three-component model, which included WIS, tumor-infiltrating lymphocytes, and HER2 positivity, was 0.92 (95% CI: 0.84, 0.99). A WIS of more than 1.6% per second was associated with higher pCR rates in the HER2-positive (OR, 21.7 [95% CI: 1.8, 260.6]; P = .02) breast cancer subgroup. For luminal HER2-negative and triple-negative breast cancers, a WIS of more than 1.6% per second was associated with low RCB (OR, 11.0 [95% CI: 1.1, 106.4]; P = .04). Conclusion The wash-in slope (WIS) assessment at initial ultrafast dynamic contrast-enhanced MRI may be used to predict pathologic complete response (pCR) in participants with breast cancer. The WIS value was used to identify two subsets of human epidermal growth factor receptor 2-positive cancers with distinct pCR rates. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee and Moy in this issue.

FAST breast magnetic resonance imaging: a new approach for breast cancer screening?

OBJECTIVE

To develop an abbreviated breast magnetic resonance imaging protocol (FAST) and to compare it with the complete protocol (FULL) to determine its diagnostic accuracy for detecting malignant or suspicious lesions (BI-RADS 4, 5 and 6) and the time required for image interpretation using BI-RADS categorization.

METHODS

Retrospective study with 100 consecutive women who underwent breast magnetic resonance imaging between January and February 2014. All patients were submitted to a complete breast magnetic resonance imaging protocol, which was then compared with an abbreviated protocol (pre-contrast sequence, second post-contrast sequence and subtraction of pre- from post-contrast images).

RESULTS

Of 100 patients, 4 were classified as BI-RADS 5 or 6 and 16 as BI-RADS 4. In these 20 patients, there was full agreement among readers regarding the final BI-RADS categorization in both (FAST and FULL) protocols.

CONCLUSION

The FAST protocol reduces interpretation time without compromising the accuracy of the method for detection of malignant or suspicious lesions.

Abbreviated Screening MRI for Women with a History of Breast Cancer: Comparison with Full-Protocol Breast MRI

Background Few studies have compared abbreviated breast MRI with full-protocol MRI in women with a personal history of breast cancer (PHBC), and they have not adjusted for confounding variables. Purpose To compare abbreviated breast MRI with full-protocol MRI in women with PHBC by using propensity score matching to adjust for confounding variables. Materials and Methods In this single-center retrospective study, women with PHBC who underwent full-protocol MRI (January 2008-August 2017) or abbreviated MRI (September 2017-April 2019) were identified. With use of a propensity score-matched cohort, screening performances were compared between the two MRI groups with the McNemar test or a propensity score-adjusted generalized estimating equation. The coprimary analyses were sensitivity and specificity. The secondary analyses were the cancer detection rate, interval cancer rate, positive predictive value for biopsies performed (PPV3), and Breast Imaging Reporting and Data System (BI-RADS) category 3 short-term follow-up rate. Results There were 726 women allocated to each MRI group (mean age ± SD, 50 years ± 8 for both groups). Abbreviated MRI and full-protocol MRI showed comparable sensitivity (15 of 15 cancers [100%; 95% CI: 78, 100] vs nine of 13 cancers [69%; 95% CI: 39, 91], respectively; P = .17). Abbreviated MRI showed higher specificity than full-protocol MRI (660 of 711 examinations [93%; 95% CI: 91, 95] vs 612 of 713 examinations [86%; 95% CI: 83, 88], respectively; P < .001). The cancer detection rate (21 vs 12 per 1000 examinations), interval cancer rate (0 vs five per 1000 examinations), and PPV3 (61% [14 of 23 examinations] vs 41% [nine of 22 examinations]) were comparable (all P < .05). The BI-RADS category 3 short-term follow-up rate of abbreviated MRI was less than half that of full-protocol MRI (5% [36 of 726 examinations] vs 12% [84 of 726 examinations], respectively; P < .001). Ninety-three percent (14 of 15) of cancers detected at abbreviated MRI were node-negative T1-invasive cancers (n = 6) or ductal carcinoma in situ (n = 8). Conclusion Abbreviated breast MRI showed comparable sensitivity and superior specificity to full-protocol MRI in breast cancer detection in women with a personal history of breast cancer. © RSNA, 2022 Online supplemental material is available for this article.

Biomimetic nanobubbles for triple-negative breast cancer targeted ultrasound molecular imaging

Triple-negative breast cancer (TNBC) is a highly heterogeneous breast cancer subtype with poor prognosis. Although anatomical imaging figures prominently for breast lesion screening, TNBC is often misdiagnosed, thus hindering early medical care. Ultrasound (US) molecular imaging using nanobubbles (NBs) capable of targeting tumor cells holds great promise for improved diagnosis and therapy. However, the lack of conventional biomarkers in TNBC impairs the development of current targeted agents. Here, we exploited the homotypic recognition of cancer cells to synthesize the first NBs based on TNBC cancer cell membrane (i.e., NB_CCM) as a targeted diagnostic agent. We developed a microfluidic technology to synthesize NB_CCM based on the self-assembly property of cell membranes in aqueous solutions. In vitro, optimal NB_CCM had a hydrodynamic diameter of 683 ± 162 nm, showed long-lasting US contrast enhancements and homotypic affinity. In vivo, we demonstrated that NB_CCM showed increased extravasation and retention in a TNBC mouse model compared to non-targeted NBs by US molecular imaging. Peak intensities and areas under the curves from time-intensity plots showed a significantly enhanced signal from NB_CCM compared to non-targeted NBs (2.1-fold, P = 0.004, and, 3.6-fold, P = 0.0009, respectively). Immunofluorescence analysis further validated the presence of NB_CCM in the tumor microenvironment. Circumventing the challenge for universal cancer biomarker identification, our approach could enable TNBC targeting regardless of tumor tissue heterogeneity, thus improving diagnosis and potentially gene/drug targeted delivery. Ultimately, our approach could be used to image many cancer types using biomimetic NBs prepared from their respective cancer cell membranes.

Breast cancer screening and early diagnosis in Chinese women

Breast cancer is the most common malignant tumor in Chinese women, and its incidence is increasing. Regular screening is an effective method for early tumor detection and improving patient prognosis. In this review, we analyze the epidemiological changes and risk factors associated with breast cancer in China and describe the establishment of a screening strategy suitable for Chinese women. Chinese patients with breast cancer tend to be younger than Western patients and to have denser breasts. Therefore, the age of initial screening in Chinese women should be earlier, and the importance of screening with a combination of ultrasound and mammography is stressed. Moreover, Chinese patients with breast cancers have several ancestry-specific genetic features, and aiding in the determination of genetic screening strategies for identifying high-risk populations. On the basis of current studies, we summarize the development of risk-stratified breast cancer screening guidelines for Chinese women and describe the significant improvement in the prognosis of patients with breast cancer in China.

ACCURACY OF ABBREVIATED PROTOCOL OF MAGNETIC RESONANCE CHOLANGIO-PANCREATOGRAPHY IN THE DIAGNOSIS OF CHOLEDOCHOLITHIASIS

BACKGROUND

Abbreviated magnetic resonance imaging protocols have emerged to reduce the examination time of the long protocols eliminating unnecessary pulse sequences to answer a targeted clinical question, without compromising diagnostic information.

OBJECTIVE

The objective of this study was to evaluate the diagnostic accuracy of an abbreviated magnetic resonance cholangiopancreatography (A-MRCP) protocol in patients with suspected choledocholithiasis.

METHODS

This retrospective study evaluated patients (ages 10 + years) that performed consecutive MRCP examination from October 2019 to June 2020, with the clinical suspicion of choledocholithiasis. Readers first evaluated the biliary tree using a four-sequence A-MRCP protocol and later reviewed the entire conventional eleven-sequence MRCP. Presence of choledocholithiasis, stone size, common bile duct caliber, and additional findings were evaluated.

RESULTS

A total of 148 patients with MRCP were included (62.8% female, mean 50.9 years). The prevalence of choledocholithiasis was 32.2%. The accuracy of the abbreviated MRCP protocol for choledocholithiasis was 98.7%. There was no difference between the performance of the abbreviated and conventional MRCP image sets for detection of choledocholithiasis (kappa=0.970), with a sensitivity of 98% and a specificity of 99%. There was excellent inter-reader agreement evaluating for choledocholithiasis on both imaging sets of MRCP protocols (kappa values were 0.970).

CONCLUSION

An abbreviated MRCP protocol to evaluate for choledocholithiasis provides similar diagnostic over the conventional MRCP protocol, offering potential for decreased scanning time and improved patient tolerability.

Small lesion classification on abbreviated breast MRI: training can improve diagnostic performance and inter-reader agreement

OBJECTIVE

To determine whether the diagnostic performance and inter-reader agreement for small lesion classification on abbreviated breast MRI (AB-MRI) can be improved by training, and can achieve the level of full diagnostic protocol MRI (FDP-MRI).

METHODS

This retrospective study enrolled 1165 breast lesions (≤ 2 cm; 409 malignant and 756 benign) from 1165 MRI examinations for reading test. Twelve radiologists were assigned into a trained group and a non-trained group. They interpreted each AB-MRI twice, which was extracted from FDP-MRI. After the first read, the trained group received a structured training for AB-MRI interpretation while the non-trained group did not. FDP-MRIs were interpreted by the trained group after the second read. BI-RADS category for each lesion was compared to the standard of reference (histopathological examination or follow-up) to calculate diagnostic accuracy. Inter-reader agreement was assessed using multirater k analysis. Diagnostic accuracy and inter-reader agreement were compared between the trained and non-trained groups, between the first and second reads, and between AB-MRI and FDP-MRI.

RESULTS

After training, the diagnostic accuracy of AB-MRI increased from 77.6 to 84.4%, and inter-reader agreement improved from 0.410 to 0.579 (both p < 0.001), which were higher than those of the non-trained group (accuracy, 84.4% vs 78.0%; weighted k, 0.579 vs 0.461; both p < 0.001). The post-training accuracy and inter-reader agreement of AB-MRI were lower than those of FDP-MRI (accuracy, 84.4% vs 92.8%; weighted k, 0.579 vs 0.602; both p < 0.001).

CONCLUSIONS

Training can improve the diagnostic performance and inter-reader agreement for small lesion classification on AB-MRI; however, it remains inferior to those of FDP-MRI.

KEY POINTS

• Training can improve the diagnostic performance for small breast lesions on AB-MRI. • Training can reduce inter-observer variation for breast lesion classification on AB-MRI, especially among junior radiologists. • The post-training diagnostic performance and inter-reader agreement of AB-MRI remained inferior to those of FDP-MRI.

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

Machine Learning Models That Integrate Tumor Texture and Perfusion Characteristics Using Low-Dose Breast Computed Tomography Are Promising for Predicting Histological Biomarkers and Treatment Failure in Breast Cancer Patients

Simple Summary

Tumor angiogenesis and heterogeneity are associated with poor prognosis for breast cancer. Advances in computer technology have made it possible to noninvasively quantify tumor angiogenesis and heterogeneity appearing in imaging data. We investigated whether low-dose CT could be used as a method for functional oncology imaging to assess tumor heterogeneity and angiogenesis in breast cancer and to predict noninvasively histological biomarkers and molecular subtypes of breast cancer. Low-dose breast CT has advantages in terms of radiation safety and patient convenience. Our study produced promising results for the use of machine learning with low-dose breast CT to identify histological prognostic factors including hormone receptor and human epidermal growth factor receptor 2 status, grade, and molecular subtype in patients with invasive breast cancer. Machine learning that integrates texture and perfusion features of breast cancer with low-dose CT can provide valuable information for the realization of precision medicine.

Abstract

This prospective study enrolled 147 women with invasive breast cancer who underwent low-dose breast CT (80 kVp, 25 mAs, 1.01–1.38 mSv) before treatment. From each tumor, we extracted eight perfusion parameters using the maximum slope algorithm and 36 texture parameters using the filtered histogram technique. Relationships between CT parameters and histological factors were analyzed using five machine learning algorithms. Performance was compared using the area under the receiver-operating characteristic curve (AUC) with the DeLong test. The AUCs of the machine learning models increased when using both features instead of the perfusion or texture features alone. The random forest model that integrated texture and perfusion features was the best model for prediction (AUC = 0.76). In the integrated random forest model, the AUCs for predicting human epidermal growth factor receptor 2 positivity, estrogen receptor positivity, progesterone receptor positivity, ki67 positivity, high tumor grade, and molecular subtype were 0.86, 0.76, 0.69, 0.65, 0.75, and 0.79, respectively. Entropy of pre- and postcontrast images and perfusion, time to peak, and peak enhancement intensity of hot spots are the five most important CT parameters for prediction. In conclusion, machine learning using texture and perfusion characteristics of breast cancer with low-dose CT has potential value for predicting prognostic factors and risk stratification in breast cancer patients.

Radiomics in breast MRI: current progress toward clinical application in the era of artificial intelligence

Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis for breast MRI, but ultrafast images, T2-weighted images, and diffusion-weighted images are also taken to improve the characteristics of the lesion. Such multiparametric MRI with numerous morphological and functional data poses new challenges to radiologists, and thus, new tools for reliable, reproducible, and high-volume quantitative assessments are warranted. In this context, radiomics, which is an emerging field of research involving the conversion of digital medical images into mineable data for clinical decision-making and outcome prediction, has been gaining ground in oncology. Recent development in artificial intelligence has promoted radiomics studies in various fields including breast cancer treatment and numerous studies have been conducted. However, radiomics has shown a translational gap in clinical practice, and many issues remain to be solved. In this review, we will outline the steps of radiomics workflow and investigate clinical application of radiomics focusing on breast MRI based on published literature, as well as current discussion about limitations and challenges in radiomics.

Dedicated breast CT: state of the art-Part II. Clinical application and future outlook

Dedicated breast CT is being increasingly used for breast imaging. This technique provides images with no compression, removal of tissue overlap, rapid acquisition, and available simultaneous assessment of microcalcifications and contrast enhancement. In this second installment in a 2-part review, the current status of clinical applications and ongoing efforts to develop new imaging systems are discussed, with particular emphasis on how to achieve optimized practice including lesion detection and characterization, response to therapy monitoring, density assessment, intervention, and implant evaluation. The potential for future screening with breast CT is also addressed. KEY POINTS: • Dedicated breast CT is an emerging modality with enormous potential in the future of breast imaging by addressing numerous clinical needs from diagnosis to treatment. • Breast CT shows either noninferiority or superiority with mammography and numerical comparability to MRI after contrast administration in diagnostic statistics, demonstrates excellent performance in lesion characterization, density assessment, and intervention, and exhibits promise in implant evaluation, while potential application to breast cancer screening is still controversial. • New imaging modalities such as phase-contrast breast CT, spectral breast CT, and hybrid imaging are in the progress of R & D.

What's Hot in Breast MRI

Several articles in the literature have demonstrated a promising role for breast MRI techniques that are more economic in total exam time than others when used as supplement to mammography for detection and diagnosis of breast cancer. There are many technical factors that must be considered in the shortened breast MRI protocols to cut down time of standard ones, including using optimal fat suppression, gadolinium-chelates intravascular contrast administrations for dynamic imaging with post processing subtractions and maximum intensity projections (MIP) high spatial and temporal resolution among others. Multiparametric breast MRI that includes both gadolinium-dependent, i.e., dynamic contrast-enhanced (DCE-MRI) and gadolinium-free techniques, i.e., diffusion-weighted/diffusion-tensor magnetic resonance imaging (DWI/DTI) are shown by several investigators that can provide extremely high sensitivity and specificity for detection of breast cancer. This article provides an overview of the proven indications for breast MRI including breast cancer screening for higher than average risk, determining chemotherapy induced tumor response, detecting residual tumor after incomplete surgical excision, detecting occult cancer in patients presenting with axillary node metastasis, detecting residual tumor after incomplete breast cancer surgical excision, detecting cancer when results of conventional imaging are equivocal, as well patients suspicious of having breast implant rupture. Despite having the highest sensitivity for breast cancer detection, there are pitfalls, however, secondary to false positive and false negative contrast enhancement and contrast-free MRI techniques. Awareness of the strengths and limitations of different approaches to obtain state of the art MR images of the breast will facilitate the work-up of patients with suspicious breast lesions.

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

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.