Multiparametric evaluation of breast lesions using PET-MRI: initial results and future perspectives

Combined Use of Shear Wave Elastography, Microvascular Doppler Ultrasound Technique, and BI-RADS for the Differentiation of Benign and Malignant Breast Masses

Objective

To evaluate the value of the combined use of Breast Imaging Reporting and Data System (BI-RADS), qualitative shear wave elastography (SWE), and AngioPLUS microvascular Doppler ultrasound technique (AP) for distinguishing benign and malignant breast masses.

Materials and Methods

A total of 210 pathologically confirmed breast lesions in 210 patients were reviewed using BI-RADS, qualitative SWE, and AP. The sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), accuracy, and area under the receiver operating characteristic curve (AUC) of BI-RADS and the combination of qualitative SWE and/or AP with BI-RADS were compared, respectively.

Results

Compared with using BI-RADS alone, the use of combined qualitative SWE and/or AP with BI-RADS had higher AUC values (P < 0.001). Besides this, the combination of qualitative SWE and AP with BI-RADS had the best diagnostic performance for differentiating between benign and malignant masses. When AP and SWE were combined with BI-RADS, 49/76 benign masses were downgraded from BI-RADS category 4a into BI-RADS category 3, while no benign masses were upgraded from BI-RADS category 3 into BI-RADS category 4a. Three sub-centimeter malignant masses were downgraded from BI-RADS category 4a into BI-RADS category 3, while three malignant masses remain in BI-RADS category 3 due to a benign manifestation in both AP and qualitative SWE. Moreover, 5/6 of them were sub-centimeter masses, and 4/6 of them were intraductal carcinoma. The sensitivity, specificity, PPV, NPV, accuracy, and AUC were 91.0%, 81.1%, 69.3%, 95.1%, 84.3%, and 0.861 (95% confidence interval, 0.806–0.916; P < 0.001), respectively. Compared with BI-RADS alone, the sensitivity slightly decreased, while the specificity, PPV, NPV, and accuracy were significantly improved.

Conclusion

Combination of qualitative SWE and AP with BI-RADS improved the diagnostic performance in differentiating benign from malignant breast lesions, which is helpful for avoiding unnecessary biopsies. However, we should be careful about the downgrading of sub-centimeter BI-RADS 4a category lesions.

Clinical advances in PET-MRI for breast cancer

Imaging is paramount for the early detection and clinical staging of breast cancer, as well as to inform management decisions and direct therapy. PET-MRI is a quantitative hybrid imaging technology that combines metabolic and functional PET data with anatomical detail and functional perfusion information from MRI. The clinical applicability of PET-MRI for breast cancer is an active area of research. In this Review, we discuss the rationale and summarise the clinical evidence for the use of PET-MRI in the diagnosis, staging, prognosis, tumour phenotyping, and assessment of treatment response in breast cancer. The continued development and approval of targeted radiopharmaceuticals, together with radiomics and automated analysis tools, will further expand the opportunity for PET-MRI to provide added value for breast cancer imaging and patient care.

AI-enhanced simultaneous multiparametric 18F-FDG PET/MRI for accurate breast cancer diagnosis

Purpose

To assess whether a radiomics and machine learning (ML) model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric ¹⁸F-FDG PET/MRI can discriminate between benign and malignant breast lesions.

Methods

A population of 102 patients with 120 breast lesions (101 malignant and 19 benign) detected on ultrasound and/or mammography was prospectively enrolled. All patients underwent hybrid ¹⁸F-FDG PET/MRI for diagnostic purposes. Quantitative parameters were extracted from DCE (MTT, VD, PF), DW (mean ADC of breast lesions and contralateral breast parenchyma), PET (SUVmax, SUVmean, and SUVminimum of breast lesions, as well as SUVmean of the contralateral breast parenchyma), and T2-weighted images. Radiomics features were extracted from DCE, T2-weighted, ADC, and PET images. Different diagnostic models were developed using a fine Gaussian support vector machine algorithm which explored different combinations of quantitative parameters and radiomics features to obtain the highest accuracy in discriminating between benign and malignant breast lesions using fivefold cross-validation. The performance of the best radiomics and ML model was compared with that of expert reader review using McNemar’s test.

Results

Eight radiomics models were developed. The integrated model combining MTT and ADC with radiomics features extracted from PET and ADC images obtained the highest accuracy for breast cancer diagnosis (AUC 0.983), although its accuracy was not significantly higher than that of expert reader review (AUC 0.868) (p = 0.508).

Conclusion

A radiomics and ML model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric ¹⁸F-FDG PET/MRI images can accurately discriminate between benign and malignant breast lesions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05492-z.

Measuring Glucose Uptake in Primary Invasive Breast Cancer Using Simultaneous Time-of-Flight Breast PET/MRI: A Method Comparison Study with Prone PET/CT

Purpose

To compare the measurement of glucose uptake in primary invasive breast cancer using simultaneous, time-of-flight breast PET/MRI with prone time-of-flight PET/CT.

Materials and Methods

In this prospective study, women with biopsy-proven invasive breast cancer undergoing preoperative breast MRI from 2016 to 2018 were eligible. Participants who had fasted underwent prone PET/CT of the breasts approximately 60 minutes after injection of 370 MBq (10 mCi) fluorine 18 fluorodeoxyglucose (18F-FDG) followed by prone PET/MRI using standard clinical breast MRI sequences performed simultaneously with PET acquisition. Volumes of interest were drawn for tumors and contralateral normal breast fibroglandular tissue to calculate standardized uptake values (SUVs). Spearman correlation, Wilcoxon signed ranked test, Mann-Whitney test, and Bland-Altman analyses were performed.

Results

Twenty-three women (mean age, 50 years; range, 33-70 years) were included. Correlation between tumor uptake values measured with PET/MRI and PET/CT was strong (r s = 0.95-0.98). No difference existed between modalities for tumor maximum SUV (SUVmax) normalized to normal breast tissue SUVmean (normSUVmax) (P = .58). The least amount of measurement bias was observed with normSUVmax, +3.86% (95% limits of agreement: -28.92, +36.64).

Conclusion

These results demonstrate measurement agreement between PET/CT, the current reference standard for tumor glucose uptake quantification, and simultaneous time-of-flight breast 18F-FDG PET/MRI.Keywords: Breast, Comparative Studies, PET/CT, PET/MR Supplemental material is available for this article. © RSNA, 2021See also the commentary by Mankoff and Surti in this issue.

Progress and Future Trends in PET/CT and PET/MRI Molecular Imaging Approaches for Breast Cancer

Breast cancer is a major disease with high morbidity and mortality in women worldwide. Increased use of imaging biomarkers has been shown to add more information with clinical utility in the detection and evaluation of breast cancer. To date, numerous studies related to PET-based imaging in breast cancer have been published. Here, we review available studies on the clinical utility of different PET-based molecular imaging methods in breast cancer diagnosis, staging, distant-metastasis detection, therapeutic and prognostic prediction, and evaluation of therapeutic responses. For primary breast cancer, PET/MRI performed similarly to MRI but better than PET/CT. PET/CT and PET/MRI both have higher sensitivity than MRI in the detection of axillary and extra-axillary nodal metastases. For distant metastases, PET/CT has better performance in the detection of lung metastasis, while PET/MRI performs better in the liver and bone. Additionally, PET/CT is superior in terms of monitoring local recurrence. The progress in novel radiotracers and PET radiomics presents opportunities to reclassify tumors by combining their fine anatomical features with molecular characteristics and develop a beneficial pathway from bench to bedside to predict the treatment response and prognosis of breast cancer. However, further investigation is still needed before application of these modalities in clinical practice. In conclusion, PET-based imaging is not suitable for early-stage breast cancer, but it adds value in identifying regional nodal disease and distant metastases as an adjuvant to standard diagnostic imaging. Recent advances in imaging techniques would further widen the comprehensive and convergent applications of PET approaches in the clinical management of breast cancer.

Multiplexed imaging for diagnosis and therapy

Complex molecular and metabolic phenotypes depict cancers as a constellation of different diseases with common themes. Precision imaging of such phenotypes requires flexible and tunable modalities capable of identifying phenotypic fingerprints by using a restricted number of parameters while ensuring sensitivity to dynamic biological regulation. Common phenotypes can be detected by in vivo imaging technologies, and effectively define the emerging standards for disease classification and patient stratification in radiology. However, for the imaging data to accurately represent a complex fingerprint, the individual imaging parameters need to be measured and analysed in relation to their wider spatial and molecular context. In this respect, targeted palettes of molecular imaging probes facilitate the detection of heterogeneity in oncogene-driven alterations and their response to treatment, and lead to the expansion of rational-design elements for the combination of imaging experiments. In this Review, we evaluate criteria for conducting multiplexed imaging, and discuss its opportunities for improving patient diagnosis and the monitoring of therapy.

Assessment of Aggressiveness of Breast Cancer Using Simultaneous 18F-FDG-PET and DCE-MRI: Preliminary Observation

PURPOSE

This study aims to investigate the feasibility of using simultaneous breast MRI and PET to assess the synergy of MR pharmacokinetic and fluorine-18 fluorodeoxyglucose (F-FDG) uptake data to characterize tumor aggressiveness in terms of metastatic burden and Ki67 status.

METHODS

Twelve consecutive patients underwent breast and whole-body PET/MRI. During the MR scan, PET events were simultaneously accumulated. MR contrast kinetic model parametric maps were computed using the extended Tofts model, including the volume transfer constant between blood plasma and the interstitial space (K), the transfer constant from the interstitial space to the blood plasma (kep), and the plasmatic volume fraction (Vp).

RESULTS

Patients with systemic metastases had a significantly lower kep compared to those with local disease (0.45 vs. 0.99 min, P = 0.011). Metastatic burden correlated positively with K and standardized uptake value (SUV), and negatively with kep. Ki67 positive tumors had a significantly greater K compared to Ki67 negative tumors (0.29 vs. 0.45 min, P = 0.03). A negative correlation was found between metabolic tumor volume and transfer constant (K or Kep).

CONCLUSION

These preliminary results suggest that MR pharmacokinetic parameters and FDG-PET may aid in the assessment of tumor aggressiveness and metastatic potential. Future studies are warranted with a larger cohort to further assess the role of pharmacokinetic modeling in simultaneous PET/MRI imaging.

Diagnostic Performance of Whole-Body PET/MRI for Detecting Malignancies in Cancer Patients: A Meta-Analysis

Background

As an evolving imaging modality, PET/MRI is preliminarily applied in clinical practice. The aim of this study was to assess the diagnostic performance of PET/MRI for tumor staging in patients with various types of cancer.

Methods

Relevant articles about PET/MRI for cancer staging were systematically searched in PubMed, EMBASE, EBSCO and the Cochrane Library. Two researchers independently selected studies, extracted data and assessed the methodological quality using the QUADAS tool. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated per patient and per lesion. The summary receiver-operating characteristic (SROC) curves were also constructed, and the area under the curve (AUC) and Q* estimates were obtained.

Results

A total of 38 studies that involved 753 patients and 4234 lesions met the inclusion criteria. On a per-patient level, the pooled sensitivity and specificity with 95% confidence intervals (CIs) were 0.93 (0.90–0.95) and 0.92 (0.89–0.95), respectively. On a per-lesion level, the corresponding estimates were 0.90 (0.88–0.92) and 0.95 (0.94–0.96), respectively. The pooled PLR, NLR and DOR estimates were 6.67 (4.83–9.19), 0.12 (0.07–0.21) and 75.08 (42.10–133.91) per patient and 10.91 (6.79–17.54), 0.13 (0.08–0.19) and 102.53 (59.74–175.97) per lesion, respectively.

Conclusion

According to our results, PET/MRI has excellent diagnostic potential for the overall detection of malignancies in cancer patients. Large, multicenter and prospective studies with standard scanning protocols are required to evaluate the diagnostic value of PET/MRI for individual cancer types.

The Diagnostic Value of Superb Microvascular Imaging (SMI) in Detecting Blood Flow Signals of Breast Lesions: A Preliminary Study Comparing SMI to Color Doppler Flow Imaging

The correlation between color Doppler flow imaging (CDFI) and Superb Microvascular Imaging (SMI) for detecting blood flow in breast lesions was investigated, as was the diagnostic value of SMI in differentiating benign from malignant breast lesions.These lesions were evaluated using both CDFI and SMI according to Adler's method. Pathologic examination showed 57 malignant lesions and 66 benign lesions. The number of blood vessels in a single mass was detected by 2 techniques (SMI and CDFI), and the difference between the 2 values (SMI-CDFI) was calculated. The optimal threshold for the diagnosis of malignant neoplasms and the diagnostic performances of SMI, CDFI, and SMI-CDFI were calculated.For the total lesions and malignant lesions alone, the difference between SMI and CDFI for detecting blood flow was significant (P < 0.01), but the difference was not significant for benign lesions (P = 0.15). The area under the receiver operating characteristic curve was 0.73 (95% confidence interval [CI]: 0.64-0.82) for CDFI; 0.81 (95% CI: 0.74-0.89) for SMI; and 0.89 (95% CI: 0.82-0.95) for SMI-CDFI. Furthermore, the modality of "SMI-CDFI" showed the best diagnostic performance.SMI provides further microvessel information in breast lesions. The diagnostic modality of "SMI-CDFI" can improve the diagnostic performance of ultrasound in the differentiation between benign and malignant masses.