Magnetization transfer ratio as a predictor of malignancy in breast lesions: Preliminary results

Confounding factors in breast magnetic resonance fingerprinting: B 1 + , slice profile, and diffusion effects

PURPOSE

Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model-based reconstruction. This study characterizes the influence of in-plane B 1 + , slice profile and diffusion effects on T₁ and T₂ estimation in the female breast at 1.5T.

METHODS

Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE.

RESULTS

Theoretic analysis predicts T₁ under-/T₂ overestimation if the nominal flip angles are underestimated and inversely, T₁ under-/T₂ overestimation if omitting slice profile correction, and T₁ under-/T₂ underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in-plane B 1 + effects occurred in vivo, causing T₂ left-right inhomogeneity between both breasts. Their correction decreased the T₂ difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T₂ most strongly, resulting in -22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions.

CONCLUSION

Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.

Magnetization Transfer MRI of Breast Cancer in the Community Setting: Reproducibility and Preliminary Results in Neoadjuvant Therapy

Repeatability and reproducibility of magnetization transfer magnetic resonance imaging of the breast, and the ability of this technique to assess the response of locally advanced breast cancer to neoadjuvant therapy (NAT), are determined. Reproducibility scans at 3 different 3 T scanners, including 2 scanners in community imaging centers, found a 16.3% difference (n = 3) in magnetization transfer ratio (MTR) in healthy breast fibroglandular tissue. Repeatability scans (n = 10) found a difference of ∼8.1% in the MTR measurement of fibroglandular tissue between the 2 measurements. Thus, MTR is repeatable and reproducible in the breast and can be integrated into community imaging clinics. Serial magnetization transfer magnetic resonance imaging performed at longitudinal time points during NAT indicated no significant change in average tumoral MTR during treatment. However, histogram analysis indicated an increase in the dispersion of MTR values of the tumor during NAT, as quantified by higher standard deviation (P = .005), higher full width at half maximum (P = .02), and lower kurtosis (P = .02). Patients' stratification into those with pathological complete response (pCR; n = 6) at the conclusion of NAT and those with residual disease (n = 9) showed wider distribution of tumor MTR values in patients who achieved pCR after 2-4 cycles of NAT, as quantified by higher standard deviation (P = .02), higher full width at half maximum (P = .03), and lower kurtosis (P = .03). Thus, MTR can be used as an imaging metric to assess response to breast NAT.

Three-dimensional MR Fingerprinting for Quantitative Breast Imaging

Purpose To develop a fast three-dimensional method for simultaneous T1 and T2 quantification for breast imaging by using MR fingerprinting. Materials and Methods In this prospective study, variable flip angles and magnetization preparation modules were applied to acquire MR fingerprinting data for each partition of a three-dimensional data set. A fast postprocessing method was implemented by using singular value decomposition. The proposed technique was first validated in phantoms and then applied to 15 healthy female participants (mean age, 24.2 years ± 5.1 [standard deviation]; range, 18-35 years) and 14 female participants with breast cancer (mean age, 55.4 years ± 8.8; range, 39-66 years) between March 2016 and April 2018. The sensitivity of the method to B₁ field inhomogeneity was also evaluated by using the Bloch-Siegert method. Results Phantom results showed that accurate and volumetric T1 and T2 quantification was achieved by using the proposed technique. The acquisition time for three-dimensional quantitative maps with a spatial resolution of 1.6 × 1.6 × 3 mm³ was approximately 6 minutes. For healthy participants, averaged T1 and T2 relaxation times for fibroglandular tissues at 3.0 T were 1256 msec ± 171 and 46 msec ± 7, respectively. Compared with normal breast tissues, higher T2 relaxation time (68 msec ± 13) was observed in invasive ductal carcinoma (P < .001), whereas no statistical difference was found in T1 relaxation time (1183 msec ± 256; P = .37). Conclusion A method was developed for breast imaging by using the MR fingerprinting technique, which allows simultaneous and volumetric quantification of T1 and T2 relaxation times for breast tissues. © RSNA, 2018 Online supplemental material is available for this article.

Quantitative Magnetization Transfer Imaging of the Breast at 3.0 T: Reproducibility in Healthy Volunteers

Quantitative magnetization transfer magnetic resonance imaging provides a means for indirectly detecting changes in the macromolecular content of tissue noninvasively. A potential application is the diagnosis and assessment of treatment response in breast cancer; however, before quantitative magnetization transfer imaging can be reliably used in such settings, the technique's reproducibility in healthy breast tissue must be established. Thus, this study aims to establish the reproducibility of the measurement of the macromolecular-to-free water proton pool size ratio (PSR) in healthy fibroglandular (FG) breast tissue. Thirteen women with no history of breast disease were scanned twice within a single scanning session, with repositioning between scans. Eleven women had appreciable FG tissue for test–retest measurements. Mean PSR values for the FG tissue ranged from 9.5% to 16.7%. The absolute value of the difference between 2 mean PSR measurements for each volunteer ranged from 0.1% to 2.1%. The 95% confidence interval for the mean difference was ±0.75%, and the repeatability value was 2.39%. These results indicate that the expected measurement variability would be ±0.75% for a cohort of a similar size and would be ±2.39% for an individual, suggesting that future studies of change in PSR in patients with breast cancer are feasible.

Incorporating dixon multi-echo fat water separation for novel quantitative magnetization transfer of the human optic nerve in vivo

PURPOSE

The optic nerve (ON) represents the sole pathway between the eyes and brain; consequently, diseases of the ON can have dramatic effects on vision. However, quantitative magnetization transfer (qMT) applications in the ON have been limited to ex vivo studies, in part because of the fatty connective tissue that surrounds the ON, confounding the magnetization transfer (MT) experiment. Therefore, the aim of this study was to implement a multi-echo Dixon fat-water separation approach to remove the fat component from MT images.

METHODS

MT measurements were taken in a single slice of the ON and frontal lobe using a three-echo Dixon readout, and the water and out-of-phase images were applied to a two-pool model in ON tissue and brain white matter to evaluate the effectiveness of using Dixon fat-water separation to remove fatty tissue from MT images.

RESULTS

White matter data showed no significant differences between image types; however, there was a significant increase (p < 0.05) in variation in the out-of-phase images in the ON relative to the water images.

CONCLUSIONS

The results of this study demonstrate that Dixon fat-water separation can be robustly used for accurate MT quantification of anatomies susceptible to partial volume effects resulting from fat. Magn Reson Med 77:707-716, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Functional MRI and CT biomarkers in oncology

Imaging biomarkers derived from MRI or CT describe functional properties of tumours and normal tissues. They are finding increasing numbers of applications in diagnosis, monitoring of response to treatment and assessment of progression or recurrence. Imaging biomarkers also provide scope for assessment of heterogeneity within and between lesions. A wide variety of functional parameters have been investigated for use as biomarkers in oncology. Some imaging techniques are used routinely in clinical applications while others are currently restricted to clinical trials or preclinical studies. Apparent diffusion coefficient, magnetization transfer ratio and native T1 relaxation time provide information about structure and organization of tissues. Vascular properties may be described using parameters derived from dynamic contrast-enhanced MRI, dynamic contrast-enhanced CT, transverse relaxation rate (R2*), vessel size index and relative blood volume, while magnetic resonance spectroscopy may be used to probe the metabolic profile of tumours. This review describes the mechanisms of contrast underpinning each technique and the technical requirements for robust and reproducible imaging. The current status of each biomarker is described in terms of its validation, qualification and clinical applications, followed by a discussion of the current limitations and future perspectives.

Correlation between equivalent cross-relaxation rate and cellular density in soft tissue tumors

OBJECTIVE

Equivalent cross-relaxation rate (ECR) imaging (ECRI), which allows quantitation of macromolecular tissue components, is a potentially useful nuclear magnetic resonance (NMR) technique for histopathological diagnosis. The purpose of this study was to compare ECR values among various histological types and assess the correlation between ECR and tumor cellular image in soft tissue tumors.

MATERIALS AND METHODS

We performed ECRI to evaluate cellular images of soft tissue tumors and tumorous lesions. Thirty-three patients who underwent evaluation with MRI and ECRI at the first visit were enrolled. Resection or biopsy was performed to obtain a histopathological diagnosis, followed by cell density measurement. ECR values of the histological subgroups were compared, and the correlation between ECR and cell density was analyzed to assess whether ECR can be used as an indicator of histological cell density.

RESULTS

ECR values for benign tumors varied widely and were not significantly different from those for malignant tumors. However, the mean ECR value was significantly higher for high-grade malignant tumors than for low-grade tumors (p < 0.01). Moreover, a positive correlation was found between ECR and cell density (r s = 0.72; p < 0.01).

CONCLUSIONS

ECR reflects the cell density and malignancy grade of a soft tissue tumor. ECRI could provide cellular imaging and useful clinical information to aid the pre-operative diagnosis of soft tissue tumors.

T(2)∗ relaxation times of intraductal murine mammary cancer, invasive mammary cancer, and normal mammary gland

PURPOSE

This study investigates the feasibility of T(2)∗ to be a diagnostic indicator of early breast cancer in a mouse model. T(2)∗ is sensitive to susceptibility effects due to local inhomogeneity of the magnetic field, e.g., caused by hemosiderin or deoxyhemoglobin. In these mouse models, unlike in patients, the characteristics of single mammary ducts containing pure intraductal cancer can be evaluated.

METHODS

The C3(1)SV40Tag mouse model of breast cancer (n = 11) and normal FVB∕N mice (n = 6) were used to measure T(2)∗ of normal mammary gland tissue, intraepithelial neoplasia, invasive cancers, mammary lymph nodes, and muscle. MRI experiments were performed on a 9.4T animal scanner. High resolution (117 microns) axial 2D multislice gradient echo images with fat suppression were acquired first to identify inguinal mammary gland. Then a multislice multigradient echo pulse sequence with and without fat suppression were performed over the inguinal mammary gland. The modulus of a complex double exponential decay detected by the multigradient echo sequence was used to fit the absolute proton free induction decay averaged over a region of interest to determine the T(2)∗ of water and fat signals.

RESULTS

The measured T(2)∗ values of tumor and muscle are similar (∼15 ms), and almost twice that of lymph nodes (∼8 ms). There was a statistically significant difference (p < 0.03) between T(2)∗ in normal mammary tissue (13.7 ± 2.9 ms) and intraductal cancers (11 ± 2.0 ms) when a fat suppression pulse was applied.

CONCLUSIONS

These are the first reported T(2)∗ measurements from single mammary ducts. The results demonstrated that T(2)∗ measurements may have utility for identifying early pre-invasive cancers in mouse models. This may inspire similar research for patients using T(2)∗ for diagnostic imaging of early breast cancer.

Classification of breast lesions pre-contrast injection using water resonance lineshape analysis

Inhomogeneously broadened, non-Lorentzian water resonances have been observed in small image voxels of breast tissue. The non-Lorentzian components of the water resonance are probably produced by bulk magnetic susceptibility shifts caused by dense, deoxygenated tumor blood vessels (the 'blood oxygenation level-dependent' effect), but can also be produced by other characteristics of local anatomy and physiology, including calcifications and interfaces between different types of tissue. Here, we tested the hypothesis that the detection of non-Lorentzian components of the water resonance with high spectral and spatial resolution (HiSS) MRI allows the classification of breast lesions without the need to inject contrast agent. Eighteen malignant lesions and nine benign lesions were imaged with HiSS MRI at 1.5 T. A new algorithm was developed to detect non-Lorentzian (or off-peak) components of the water resonance. After a Lorentzian fit had been subtracted from the data, the largest peak in the residual spectrum in each voxel was identified as the major off-peak component of the water resonance. The difference in frequency between these off-peak components and the main water peaks, and their amplitudes, were measured in malignant lesions, benign lesions and breast fibroglandular tissue. Off-peak component frequencies were significantly different between malignant and benign lesions (p < 0.001). Receiver operating characteristic (ROC) analysis was used to assess the diagnostic performance of HiSS off-peak component analysis compared with dynamic contrast-enhanced (DCE) MRI parameters. The areas under the ROC curves for the 'DCE rapid uptake fraction', 'DCE washout fraction', 'off-peak component amplitude' and 'off-peak component frequency' were 0.75, 0.83, 0.50 and 0.86, respectively. These results suggest that water resonance lineshape analysis performs well in the classification of breast lesions without contrast injection and could improve the diagnostic accuracy of clinical breast MR examinations. In addition, this approach may provide an alternative to DCE MRI in women who are at risk for adverse reactions to contrast media.

Differentiation of malignant and benign breast lesions using magnetization transfer imaging and dynamic contrast-enhanced MRI

PURPOSE

To evaluate feasibility of using magnetization transfer ratio (MTR) in conjunction with dynamic contrast-enhanced MRI (DCE-MRI) for differentiation of benign and malignant breast lesions at 3 Tesla.

MATERIALS AND METHODS

This prospective study was IRB and HIPAA compliant. DCE-MRI scans followed by MT imaging were performed on 41 patients. Regions of interest (ROIs) were drawn on co-registered MTR and DCE postcontrast images for breast structures, including benign lesions (BL) and malignant lesions (ML). Initial enhancement ratio (IER) and delayed enhancement ratio (DER) were calculated, as were normalized MTR, DER, and IER (NMTR, NDER, NIER) values. Diagnostic accuracy analysis was performed.

RESULTS

Mean MTR in ML was lower than in BL (P < 0.05); mean DER and mean IER in ML were significantly higher than in BL (P < 0.01, P < 0.001). NMTR, NDER, and NIER were significantly lower in ML versus BL (P < 0.007, P < 0.001, P < 0.001). IER had highest diagnostic accuracy (77.6%), sensitivity (86.2%), and area under the ROC curve (.879). MTR specificity was 100%. Logistic regression modeling with NMTR and NIER yielded best results for BL versus ML (sensitivity 93.1%, specificity 80%, AUC 0.884, accuracy 83.7%).

CONCLUSION

Isolated quantitative DCE analysis may increase specificity of breast MR for differentiating BL and ML. DCE-MRI with NMTR may produce a robust means of evaluating breast lesions.

Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy

Reliable early assessment of breast cancer response to neoadjuvant therapy (NAT) would provide considerable benefit to patient care and ongoing research efforts, and demand for accurate and noninvasive early-response biomarkers is likely to increase. Response assessment techniques derived from quantitative magnetic resonance imaging (MRI) hold great potential for integration into treatment algorithms and clinical trials. Quantitative MRI techniques already available for assessing breast cancer response to neoadjuvant therapy include lesion size measurement, dynamic contrast-enhanced MRI, diffusion-weighted MRI, and proton magnetic resonance spectroscopy. Emerging yet promising techniques include magnetization transfer MRI, chemical exchange saturation transfer MRI, magnetic resonance elastography, and hyperpolarized MR. Translating and incorporating these techniques into the clinical setting will require close attention to statistical validation methods, standardization and reproducibility of technique, and scanning protocol design.

Using magnetic resonance imaging and spectroscopy in cancer diagnostics and monitoring: preclinical and clinical approaches

Nuclear Magnetic Resonance (MR) based imaging has become an integrated domain in today's oncology research and clinical management of cancer patients. MR is a unique imaging modality among numerous other imaging modalities by providing access to anatomical, physiological, biochemical and molecular details of tumour with excellent spatial and temporal resolutions. In this review we will cover established and investigational MR imaging (MRI) and MR spectroscopy (MRS) techniques used for cancer imaging and demonstrate wealth of information on tumour biology and clinical applications MR techniques offer for oncology research both in preclinical and clinical settings. Emphasis is given not only to the variety of information which may be obtained but also the complementary nature of the techniques. This ability to determine tumour type, grade, invasiveness, degree of hypoxia, microvacular characteristics, and metabolite phenotype, has already profoundly transformed oncology research and patient management. It is evident from the data reviewed that MR techniques will play a key role in uncovering molecular fingerprints of cancer, developing targeted treatment strategies and assessing responsiveness to treatment for personalized patient management, thereby allowing rapid translation of imaging research conclusions into the benefit of clinical oncology.

MRI & MRS assessment of the role of the tumour microenvironment in response to therapy

MRI and MRS techniques are being applied to the characterisation of various aspects of the tumour microenvironment and to the assessment of tumour response to therapy. For example, kinetic parameters describing tumour blood vessel flow and permeability can be derived from dynamic contrast-enhanced MRI data and have been correlated with a positive tumour response to antivascular therapies. The ongoing development and validation of noninvasive, high-resolution anatomical/molecular MR techniques will equip us with the means to detect specific tumour biomarkers early on, and then to monitor the efficacy of cancer treatments efficiently and reliably, all within a clinically relevant time frame. Reliable tumour microenvironment imaging biomarkers will provide obvious advantages by enabling tumour-specific treatment tailoring and potentially improving patient outcome. However, for routine clinical application across many disease types, such imaging biomarkers must be quantitative, robust, reproducible, sufficiently sensitive and cost-effective. These characteristics are all difficult to achieve in practice, but image biomarker development and validation have been greatly facilitated by an increasing number of pertinent preclinical in vivo cancer models. Emphasis must now be placed on discovering whether the preclinical results translate into an improvement in patient care and, therefore, overall survival.