Keywords: Breast, Breast

Motivation: Breast MRI typically is performed with a patient in the prone position.  Imaging supine would dramatically improve patient comfort and possibly reduce setup and positioning times.

Goal(s): Compare image quality in breast MRI between the supine and prone positions with specialized coils using signal-to-noise ratio.

Approach: To account for tissue deformation between supine and prone positions, we compare “tissue-independent” relative SNR, which uses the body coil SNR as a reference, in the breast tissue between prone and supine.

Results: In multiple patients, the supine position consistently showed an improvement in SNR over the prone position.

Impact: Improvements in motion correction approaches and development of flexible coils may enable supine breast imaging, which is much more comfortable for the patient than prone imaging.  Using a careful comparison, we demonstrate substantially higher SNR in supine imaging.

Keywords: MR-Guided Interventions, Fat, lipid composition, early response, neoadjuvant chemotherapy

Motivation: Deregulation of lipid composition, holding a critical role in breast cancer progression, can be accurately mapped using chemical shift-encoded imaging (CSEI), and might support response monitoring in patients undergoing neoadjuvant chemotherapy (NACT). 

Goal(s): We aimed to determine the power of CSEI in differentiation of poor responders after one cycle of NACT.

Approach: Seventeen patients were imaged before and after one cycle of NACT to compute the percentage change in monounsaturated, polyunsaturated and saturated fatty acids.

Results: There was a treatment induced lipid normalisation in all participants, however there was no difference in poor responders in comparison to good responders. 

Impact: CSEI is sensitive to the longitudinal change in lipid composition in the peri-tumoural region and the whole breast, however the impact on lipid metabolism is secondary to determining poor responder and other markers of metabolic imaging should be explored.

Keywords: Breast, Breast, Diffusion, Distortion Correction

Motivation: DW-MRI holds great potential in improving specificity in breast cancer screening (BCS). This technique uses Echo-Planar imaging (EPI) and is sensitive to distortion due to spatial magnetic inhomogeneity. Correcting such distortion is key, especially when evaluating quantitative biomarkers.

Goal(s): To study multi b-value Reverse Polarity Gradient (mRPG), originally developed for prostate DWI (abstract #4789), in comparison to standard RPG and FSL topup.

Approach: A breast phantom scan and a BCS patient dataset were distortion corrected with the three methods.

Results: mRPG showed better performance than RPG and topup, especially in ADC maps where they yield a misleading improvement of EPI distortions.

Impact: mRPG demonstrated improved performance compared to RPG and topup in correcting distortions. Normalizing DWI volumes across b-values eliminates intensity changes resulting from distortions and solves overfitting issue where Jacobian intensity correction (JIC) makes up for underestimation of tissue displacement.

Keywords: Breast, Cancer, Breast, Response, Chemotherapy

Motivation: To achieve de-escalation of surgery in breast cancer patients having complete response after primary chemotherapy, we require better accuracy than the current gold standard DCE-MRI, which has a sensitivity of 80-90% and a specificity of 37-97%. 

Goal(s): Investigate the diagnostic value of biomechanical imaging biomarkers quantified via MR-Elastography (MRE) for gauging complete pathological response non-invasively.

Approach: Incorporate MRE into standard Breast MRI protocol for NACT patients within standard-of-care MRI protocol.

Results: Biomechanical changes in conjunction with DCE MRI improved sensitivity to 94.4% and specificity to 95.7%, making this approach a promising new concept to predict complete response after NACT.

Impact: Quantifying biomechanics throughout chemotherapy via MR-Elastography (MRE) in conjunction with DCE-MRI in breast cancer patients undergoing primary chemotherapy yields more accurate results in predicting complete pathological response than current international imaging gold standard methods.

Keywords: Breast, Elastography

Motivation: While breast tumors can be identified and characterized through biopsy, MR Elastography (MRE) could provide a method of diagnosis with similar sensitivity and specificity while being non-invasive.

Goal(s): Validate the use of MRE against histological grading in biopsy and contrast enhanced MRI breast tumors.

Approach: MRE was performed on patients with known breast tumors to measure the stiffness non-invasively and validate it against biopsy.

Results: Statistically significant correlation was determined between MRE-derived tumor stiffness and histological grade of biopsy.

Impact: The statistically significant association between breast MRE results, a non-invasive method of breast cancer diagnosis, and histological grading, an invasive method, invites the possibility that physicians could diagnose breast cancer non-invasively through further study.

Keywords: Breast, Breast

Motivation: Accurately evaluating the ALN status is pivotal for both prognosis and treatment planning, especially in the context of decreasing axillary surgery.

Goal(s): This retrospective study aimed to develop a radiomics nomogram for preoperative prediction of ALN status in clinical T1-2 stage invasive breast cancer patients.

Approach: Radiomics features were extracted from ultrafast DCE-MRI and DWI, and clinical characteristics were incorporated to construct a radiomics nomogram.

Results: A radiomics signature achieved AUCs of 0.831 and 0.821 in training and validation cohorts, respectively. The radiomics nomogram, incorporating this signature, multifocality, and MRI-reported ALN status, showed superior performance with AUCs of 0.890 and 0.905.

Impact: The proposed nomogram could be valuable for noninvasively assessing ALN status, aiding prognosis and treatment planning while reducing the need for axillary surgery in breast cancer patients.

Keywords: Breast, Breast, ultrafast DCE MRI

Motivation: To know the factors affecting optimal timing of lesion evaluation in ultrafast (UF)- DCE MRI other than BPE.

Goal(s): To investigated the optimal timing for lesion depiction on UF-DCE MRI in relation to lesion size and invasive breast cancer subtype.

Approach: Optimal timing of lesion evaluation over 400 lesions were assessed by experienced readers. Its association with lesion size and subtype were examined.

Results: Optimal timing of breast lesion evaluation on UF-DCE MRI can be earlier for those with larger lesion, and not affected by subtype in case of invasive carcinoma.

Impact: UF-DCE MRI normally involves hundreds of images with multiple timing. Predicting optimal timing before scanning may help in efficient reading, efficient post-processing/reconstruction, and protocol improvement. The current results indicate the impact of lesion size, not subtype on optimal timing.

Keywords: Breast, Breast

Motivation: Kaiser score (KS) could help diagnose lesions of breast MRI by an intuitive flowchart. 

Goal(s): To compare the diagnostic performance of BI-RADS and KS and to evaluate the benefit of the modified KS+ by incorporating diffusion.

Approach: 630 patients were analyzed independently by three radiologists with different experiences, including 458 mass and 172 non-mass enhancement (NME) lesions.

Results: KS outperforms the unstructured BI-RADS, especially for less experienced readers. The diagnosis for NME was more difficult than for masses, true for three readers regardless of the method used. The accuracy of KS+ was improved for masses, but not for NME.

Impact: Kaiser Score provides an intuitive method for lesion interpretation, primarily helpful for mass lesions read by less experienced readers. KS+ is mainly applicable to mass lesions. For NME, the KS criteria need to be improved.

Keywords: Breast, Diffusion/other diffusion imaging techniques, time-dependent diffusion weighted imaging

Motivation:  Recent advances in time-dependent diffusion MRI (td-dMRI) for microstructural modeling provide the opportunity to characterize cancer pathology in vivo. 

Goal(s): This study aims to evaluate the accuracy of td-dMRI–based microstructural mapping for noninvasively characterizing of breast tumors, and further to evaluated whether the tumor microstructural properties could be used to distinguish prognostic factors in breast cancer.

Approach:  All patients underwent T1-weighted imaging, T2-weighted imaging, diffusion weighted imaging, td-dMRI, and dynamic contrast enhancement scans on a 3T scanner.

Results: Results showed that td-MRI parameters showed significant differences between benign and malignant breast tumors, and can also be used for prediction of prognostic factors in breast cancer.

Impact: The cellular microstructural mapping by time-dependent diffusion MRI show great potential for noninvasive evaluation of pathologic characteristics in breast cancer in a clinical setting.

Keywords: Breast, Quantitative Imaging, Pharmacokinetic analysis, ultrafast DCE-MRI, DCIS grading, DCIS upgrade

Motivation: Accurate grading and predicting the upgrade of DCIS can assist in surgical planning. 

Goal(s): This study investigates whether the pharmacokinetic parameters from ultrafast DCE-MRI can differentiate DCIS grade and predict the upgrade of DCIS at surgery. 

Approach: We reviewed data from 35 patients with DCIS who underwent a protocol that included preoperative ultrafast DCE-MRI (temporal resolution = 3-9 seconds) for the first minute after contrast administration. We measured pharmacokinetic parameters in DCIS from ultrafast images. 

Results: The results show that K_ep separates low-grade DCIS from intermediate and high-grade DCIS. High-grade DCIS with short bolus arrival time is associated with an upgrade to IDC.

Impact: Pharmacokinetic analysis of ultrafast DCE-MRI could distinguish low-grade DCIS from non-low-grade DCIS and could predict upgrade of high-grade DCIS to IDC.

Keywords: Breast, Breast

Motivation: There is an unmet need for noninvasive imaging biomarkers for accurate early prediction of therapy response in patients with triple negative breast cancer.

Goal(s): In this study, we investigated using a 3D convolutional neural network to predict response from quantitative T1, T2, and PD images acquired with the SyntheticMR technique.

Approach: A ResNet-101 network was extended to 3D with 3 channels of inputs, and trained and evaluated using 5-fold cross validation with 217 image datasets acquired after 2 and 4 cycles of therapy.
 

Results: Accuracy of response prediction ranged from 0.61-0.77 and dice similarity ranged from 0.68-0.77 when all time points were utilized.

Impact: Therapy response at mid-treatment may be determined by a neural network applied to a single multi-parameter mapping sequence, which may help guide treatment strategies for improved outcomes for patients with triple negative breast cancer. 

Keywords: Breast, Cancer, Breast Cancer; Molecular subtype; Dynamic contrast-enhanced; Non-mono-exponential model; Deep neural network

Motivation: Breast cancer exhibits diverse molecular subtypes with varying responses to treatment.

Goal(s): This study aims to explore the potential enhancement of breast cancer molecular subtype prediction by combining DCE and NME-DWI through DNNs.

Approach: 475 patients with 480 breast cancers were recruited and classified into molecular subtypes using IHC staining and FISH examination. Manual lesion segmentation and analysis using IVIM, diffusion kurtosis, and stretched exponential models. DNN models for molecular subtype prediction, based on single DCE-MRI or NME-DWI datasets were constructed and compared.

Results: DNN classification accuracy significantly varied among the three imaging datasets (P < 0.05), with MP-MRI outperforming DCE-MRI and NME-DWI.

Impact: This study's integration of DCE-MRI and NME-DWI through DNNs for breast cancer subtype prediction advances non-invasive genotyping, potentially transforming personalized treatment strategies and improving outcomes in breast cancer patients.

Keywords: Breast, Breast, breast cancer, human epidermal growth factor receptor 2 (HER2), magnetic resonance imaging, synthetic imaging

Motivation: Half of breast cancers exhibits HER2 low-expressing and benefits from new antibody-drug conjugates. However, it remains lack of non-invasive technique to identify HER2 expression level. T1, T2, and proton density (PD) are quantitative MRI parameters widely used to characterize tumors. 

Goal(s): Investigate if T1, T2, and PD extracted from synthetic MRI (syMRI) can be used to classify HER2 expression level.

Approach: One-hundred patients were enrolled. T1, T2, and PD of tumor were extracted from syMRI and were compared among different HER2 expression level. ROC was used to assess the diagnostic performance. 

Results: T1 and PD can be used to diagnose HER2 expression levels.

Impact: Our results suggested quantitative SyMRI can be used as non-invasive biomarker to classify HER2 zero-, low- and over-expressing breast cancer patients. It would be helpful in guiding treatment selection and dynamically monitoring HER2 expressing status during treatment process over time.  

Keywords: Breast, Breast

Motivation: Breast MRI is performed prone and has not been optimized for supine treatment position and with the personalized radiation mold, limiting application for radiation treatment monitoring

Goal(s): To evaluate the image quality and tumor size accuracy from short supine breast MRI (ssbMRI).

Approach: ssbMRI studies were acquired before and after neoadjuvant radiotherapy along with mammography and ultrasound in 20 patients. Image quality of ssbMRI was evaluated by expert readers and image derived tumor sizes were correlated with other imaging modalities and final pathology.

Results: ssbMR had acceptable image quality in 70% of the cases and best correlation with pathology.

Impact: Breast MRI in supine positioning is of diagnostic quality despite the technical challenges for patients with breast cancer.  This pilot study allows the development of a short supine diagnostic breast MRI for radiation planning and possibly fusion with CT.

Keywords: Breast, Data Acquisition, Breast, Diffusion

Motivation: Current image quality limitations of conventional diffusion weighted sequences in the breast offer an exciting opportunity for novel acquisitions that can generate distortion-free images within clinically feasible scan times.

Goal(s): To test a novel TSE-based 3D DWI sequence (VD-CASPR) in the breast of healthy volunteers and assess image quality with an incorporated phase correction algorithm.

Approach: Four healthy volunteers were scanned with current reference standard DW-EPI and DW-TSE for breast serving as benchmark for our 3D DWI sequence.

Results: Our VD-CASPR sequence with phase correction was able to generate high quality images at various b-values within shorter scan times compared to DW-TSE.

Impact: Our novel 3D DWI sequence and reconstruction pipeline generated high SNR images free of geometric distortions in the breast of healthy volunteers. Volumetric coverage without geometric distortion can facilitate co-registration with anatomical images for improved tumor characterization.

Keywords: Breast, Permeability, Breast, neoadjuvant chemotherapy, DCE

Motivation: Investigate water exchange rate constant (k_io) in monitoring breast cancer (BC) response to neoadjuvant chemotherapy (NAC).

Goal(s): Evaluate changes in k_io and voxel fraction of filtered k_io during NAC.

Approach: BC patients treated with NAC underwent longitudinal high spatiotemporal resolution DCE-MRI at three sites using different 3T vendor systems. Voxel k_io values were obtained with the shutter-speed modeling and filtered with a biologically relevant and DCE achievable range.  

Results: Fractions of filtered k_io decreased throughout the NAC course. Tumor k_io and its heterogeneity were reduced in the pathologic complete response (pCR) group compared to the non-pCR group at midpoint and end of NAC.  

Impact: Quantitative high spatiotemporal resolution Shutter-Speed Model (SSM) DCE-MRI can be implemented in multi-center and multi-platform settings with the SSM-exclusive k_io parameter providing potentially complementary information to the conventional K^trans parameter in assessment of BC response to NAC.