MIP image derived from abbreviated breast MRI: potential to reduce unnecessary sub-nipple biopsies during nipple-sparing mastectomy for breast cancer

Smart forecasting of artifacts in contrast-enhanced breast MRI before contrast agent administration

OBJECTIVES

To evaluate whether artifacts on contrast-enhanced (CE) breast MRI maximum intensity projections (MIPs) might already be forecast before gadolinium-based contrast agent (GBCA) administration during an ongoing examination by analyzing the unenhanced T1-weighted images acquired before the GBCA injection.

MATERIALS AND METHODS

This IRB-approved retrospective analysis consisted of n = 2884 breast CE MRI examinations after intravenous administration of GBCA, acquired with n = 4 different MRI devices at different field strengths (1.5 T/3 T) during clinical routine. CE-derived subtraction MIPs were used to conduct a multi-class multi-reader evaluation of the presence and severity of artifacts with three independent readers. An ensemble classifier (EC) of five DenseNet models was used to predict artifacts for the post-contrast subtraction MIPs, giving as the input source only the pre-contrast T1-weighted sequence. Thus, the acquisition directly preceded the GBCA injection. The area under ROC (AuROC) and diagnostics accuracy scores were used to assess the performance of the neural network in an independent holdout test set (n = 285).

RESULTS

After majority voting, potentially significant artifacts were detected in 53.6% (n = 1521) of all breast MRI examinations (age 49.6 ± 12.6 years). In the holdout test set (mean age 49.7 ± 11.8 years), at a specificity level of 89%, the EC could forecast around one-third of artifacts (sensitivity 31%) before GBCA administration, with an AuROC = 0.66.

CONCLUSION

This study demonstrates the capability of a neural network to forecast the occurrence of artifacts on CE subtraction data before the GBCA administration. If confirmed in larger studies, this might enable a workflow-blended approach to prevent breast MRI artifacts by implementing in-scan personalized predictive algorithms.

CLINICAL RELEVANCE STATEMENT

Some artifacts in contrast-enhanced breast MRI maximum intensity projections might be predictable before gadolinium-based contrast agent injection using a neural network.

KEY POINTS

• Potentially significant artifacts can be observed in a relevant proportion of breast MRI subtraction sequences after gadolinium-based contrast agent administration (GBCA). • Forecasting the occurrence of such artifacts in subtraction maximum intensity projections before GBCA administration for individual patients was feasible at 89% specificity, which allowed correctly predicting one in three future artifacts. • Further research is necessary to investigate the clinical value of such smart personalized imaging approaches.

Abbreviated breast MRI for evaluating breast cancer before initiation of neoadjuvant chemotherapy: A cross-sectional study

Background

Although, there are accumulating evidence about diagnostic role of abbreviated breast magnetic resonance imaging (MRI) in screening setting, the implementation of abbreviated MRI in staging of breast cancer has been poorly elucidated.

Objective

To evaluate the diagnostic performance of abbreviated breast MRI in estimating extent of disease before initiation of neoadjuvant chemotherapy.

Methods

A total of 54 patients with biopsy-proven main lesion referred to evaluate by standard protocol breast MRI before initiation of neoadjuvant chemotherapy were retrospectively enrolled. From a standard protocol, a data set of abbreviated protocol consisting fat-saturated T1-weighted (T1W) pre-contrast and first two fat-saturated T1W post-contrast series with reconstruction of their subtraction including maximum intensity projection (MIP) were obtained and interpreted. The concordance rate of abbreviated with standard protocol (as a reference standard) were compared. Diagnostic accuracy, sensitivity, specificity, and positive and negative predictive value were calculated, as well.

Results

The maximum size of the main mass was 38.6 ± 17.3 and 40.7 ± 17.9 for abbreviated and standard protocol, respectively. All of the main mass was detected by abbreviated protocol with 100% concordance. Concordance was 98.1% and 94.4% in terms of multifocal/multicentric status and for estimating of NME, respectively. The abbreviated protocol has high sensitivity and specificity with more than 90% value regarding main mass detection, measurement of the maximum size of the main mass, determination of multifocal/multicenter status and NAC involvement.

Conclusion

Abbreviated protocol may be a reliable surrogate for standard protocol breast MRI in evaluating extent of breast cancer.

Diagnostic Accuracy of Magnetic Resonance Imaging Features and Tumor-to-Nipple Distance for the Nipple-Areolar Complex Involvement of Breast Cancer: A Systematic Review and Meta-Analysis

OBJECTIVE

This systematic review and meta-analysis evaluated the accuracy of preoperative breast magnetic resonance imaging (MRI) features and tumor-to-nipple distance (TND) for diagnosing occult nipple-areolar complex (NAC) involvement in breast cancer.

MATERIALS AND METHODS

The MEDLINE, Embase, and Cochrane databases were searched for articles published until March 20, 2022, excluding studies of patients with clinically evident NAC involvement or those treated with neoadjuvant chemotherapy. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Two reviewers independently evaluated studies that reported the diagnostic performance of MRI imaging features such as continuity to the NAC, unilateral NAC enhancement, non-mass enhancement (NME) type, mass size (> 20 mm), and TND. Summary estimates of the sensitivity and specificity curves and the summary receiver operating characteristic (SROC) curve of the MRI features for NAC involvement were calculated using random-effects models. We also calculated the TND cutoffs required to achieve predetermined specificity values.

RESULTS

Fifteen studies (n = 4002 breast lesions) were analyzed. The pooled sensitivity and specificity (with 95% confidence intervals) for NAC involvement diagnosis were 71% (58-81) and 94% (91-96), respectively, for continuity to the NAC; 58% (45-70) and 97% (95-99), respectively, for unilateral NAC enhancement; 55% (46-64) and 83% (75-88), respectively, for NME type; and 88% (68-96) and 58% (40-75), respectively, for mass size (> 20 mm). TND had an area under the SROC curve of 0.799 for NAC involvement. A TND of 11.5 mm achieved a predetermined specificity of 85% with a sensitivity of 64%, and a TND of 12.3 mm yielded a predetermined specificity of 83% with a sensitivity of 65%.

CONCLUSION

Continuity to the NAC and unilateral NAC enhancement may help predict occult NAC involvement in breast cancer. To achieve the desired diagnostic performance with TND, a suitable cutoff value should be considered.

Hypertrophic breasts versus normal-sized breasts: Comparison of blood supply to the nipple-areola complex based on DCE-MRI

BACKGROUND

Understanding the blood supply to the nipple-areola complex (NAC) in hypertrophic breasts is essential to reduce the risk of NAC necrosis during reduction mammaplasty. The aim of this study was to use dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to determine the NAC blood supply of hypertrophic breasts compared with normal-sized breasts.

METHODS

DCE-MRI images of 100 Asian women (100 hypertrophic breasts and 100 normal-sized breasts) were included retrospectively. All vessels supplying the NAC were identified using axial, coronal, and sagittal maximum-intensity projection images. The diameter, length, and distance to the skin surface of source vessels were measured.

RESULTS

The number of source vessels in the hypertrophic breasts was larger than that in the normal-sized breasts. 97.0% of hypertrophic breasts had multizone blood supply to the NAC. In hypertrophic and normal-sized breasts, the proportion of vessels was highest in the supermedial zone, followed by the superolateral zone and central zone. The diameter of medial and lateral vessels was significantly increased in hypertrophic breasts. Besides, the length of source vessels in hypertrophic breasts was larger than that in normal-sized breasts.

CONCLUSIONS

Hypertrophic breasts tend to have a richer blood supply to the NAC than normal-sized breasts. The predominant vessels supplying the NAC of hypertrophic breasts are the superomedial, followed by the superolateral and central.

LEVEL OF EVIDENCE

IV.

Predicting lymphovascular invasion in clinically node-negative breast cancer detected by abbreviated magnetic resonance imaging: Transfer learning vs. radiomics

Objective

To compare the performance of abbreviated breast magnetic resonance imaging (AB-MRI)-based transfer learning (TL) algorithm and radionics analysis for lymphovascular invasion (LVI) prediction in patients with clinically node-negative invasive breast cancer (IBC).

Methods

Between November 2017 and October 2020, 233 clinically node-negative IBCs detected by AB-MRI were retrospectively enrolled. One hundred thirty IBCs from center 1 (37 LVI-positive and 93 LVI-negative) were assigned as the training cohort and 103 from center 2 (25 LVI-positive and 78 LVI-negative) as the validation cohort. Based on AB-MRI, a TL signature (TLS) and a radiomics signature (RS) were built with the least absolute shrinkage and selection operator (LASSO) logistic regression. Their diagnostic performances were validated and compared using areas under the receiver operating curve (AUCs), net reclassification improvement (NRI), integrated discrimination improvement (IDI), decision curve analysis (DCA), and stratification analysis. A convolutional filter visualization technique was used to map the response areas of LVI on the AB-MRI.

Results

In the validation cohort, compared with RS, the TLS showed better capability in discriminating LVI-positive from LVI-negative lesions (AUC: 0.852 vs. 0.726, p < 0.001; IDI = 0.092, p < 0.001; NRI = 0.554, p < 0.001). The diagnostic performance of TLS was not affected by the menstrual state, molecular subtype, or contrast agent type (all p > 0.05). Moreover, DCA showed that the TLS added more net benefit than RS for clinical utility.

Conclusions

An AB-MRI-based TLS was superior to RS for preoperative LVI prediction in patients with clinically node-negative IBC.

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.