Diffusion‐weighted breast MRI of malignancies with submillimeter resolution and immunity to artifacts by spatiotemporal encoding at 3T

Diffusion-Weighted Imaging for Skin Pathologies of the Breast-A Feasibility Study

Several breast pathologies can affect the skin, and clinical pathways might differ significantly depending on the underlying diagnosis. This study investigates the feasibility of using diffusion-weighted imaging (DWI) to differentiate skin pathologies in breast MRIs. This retrospective study included 88 female patients who underwent diagnostic breast MRI (1.5 or 3T), including DWI. Skin areas were manually segmented, and the apparent diffusion coefficients (ADCs) were compared between different pathologies: inflammatory breast cancer (IBC; n = 5), benign skin inflammation (BSI; n = 11), Paget's disease (PD; n = 3), and skin-involved breast cancer (SIBC; n = 11). Fifty-eight women had healthy skin (H; n = 58). The SIBC group had a significantly lower mean ADC than the BSI and IBC groups. These differences persisted for the first-order features of the ADC (mean, median, maximum, and minimum) only between the SIBC and BSI groups. The mean ADC did not differ significantly between the BSI and IBC groups. Quantitative DWI assessments demonstrated differences between various skin-affecting pathologies, but did not distinguish clearly between all of them. More extensive studies are needed to assess the utility of quantitative DWI in supplementing the diagnostic assessment of skin pathologies in breast imaging.

Breast MRI in patients with implantable loop recorder: initial experience

OBJECTIVES

To investigate the feasibility of breast MRI exams and guided biopsies in patients with an implantable loop recorder (ILR) as well as the impact ILRs may have on image interpretation.

MATERIALS AND METHODS

This retrospective study examined breast MRIs of patients with ILR, from April 2008 to September 2022. Radiological reports and electronic medical records were reviewed for demographic characteristics, safety concerns, and imaging findings. MR images were analyzed and compared statistically for artifact quantification on the various pulse sequences.

RESULTS

Overall, 40/82,778 (0.049%) MRIs during the study period included ILR. All MRIs were completed without early termination. No patient-related or device-related adverse events occurred. ILRs were most commonly located in the left lower-inner quadrant (64.6%). The main artifact was a signal intensity (SI) void in a dipole formation in the ILR bed with or without areas of peripheral high SI. Artifacts appeared greatest in the cranio-caudal axis (p < 0.001), followed by the anterior-posterior axis (p < 0.001), and then the right-left axis. High peripheral rim-like SI artifacts appeared on the post-contrast and subtracted T1-weighted images, mimicking suspicious enhancement. Artifacts were most prominent on diffusion-weighted (p < 0.001), followed by T2-weighted and T1-weighted images. In eight patients, suspicious findings were found on MRI, resulting in four additional malignant lesions. Of six patients with left breast cancer, the tumor was completely visible in five cases and partially obscured in one.

CONCLUSION

Breast MRI is feasible and safe among patients with ILR and may provide a significant diagnostic value, albeit with localized, characteristic artifacts.

CLINICAL RELEVANCE STATEMENT

Indicated breast MRI exams and guided biopsies can be safely performed in patients with implantable loop recorder. Nevertheless, radiologists should be aware of associated limitations including limited assessment of the inner left breast and pseudo-enhancement artifacts.

KEY POINTS

• Breast MRI in patients with an implantable loop recorder is an infrequent, feasible, and safe procedure. • Despite limited breast visualization of the implantable loop recorder bed and characteristic artifacts, MRI depicted additional lesions in 8/40 (20%) of cases, half of which were malignant. • Breast MRI in patients with an implantable loop recorder should be performed when indicated, taking into consideration typical associated artifacts.

Multishot Diffusion-Weighted MRI of the Breasts in the Supine vs. Prone Position

BACKGROUND

Diffusion-weighted imaging (DWI) may allow for breast cancer screening MRI without a contrast injection. Multishot methods improve prone DWI of the breasts but face different challenges in the supine position.

PURPOSE

To establish a multishot DWI (msDWI) protocol for supine breast MRI and to evaluate the performance of supine vs. prone msDWI.

STUDY TYPE

Prospective.

POPULATION

Protocol optimization: 10 healthy women (ages 22-56), supine vs. prone: 24 healthy women (ages 22-62) and five women (ages 29-61) with breast tumors.

FIELD STRENGTH/SEQUENCE

3-T, protocol optimization msDWI: free-breathing (FB) 2-shots, FB 4-shots, respiratory-triggered (RT) 2-shots, RT 4-shots, supine vs. prone: RT 4-shot msDWI, T2-weighted fast-spin echo.

ASSESSMENT

Protocol optimization and supine vs. prone: three observers performed an image quality assessment of sharpness, aliasing, distortion (vs. T2), perceived SNR, and overall image quality (scale of 1-5). Apparent diffusion coefficients (ADCs) in fibroglandular tissue (FGT) and breast tumors were measured.

STATISTICAL TESTS

Effect of study variables on dichotomized ratings (4/5 vs. 1/2/3) and FGT ADCs were assessed with mixed-effects logistic regression. Interobserver agreement utilized Gwet's agreement coefficient (AC). Lesion ADCs were assessed by Bland-Altman analysis and concordance correlation (ρc ). P value <0.05 was considered statistically significant.

RESULTS

Protocol optimization: 4-shots significantly improved sharpness and distortion; RT significantly improved sharpness, aliasing, perceived SNR, and overall image quality. FGT ADCs were not significantly different between shots (P = 0.812), FB vs. RT (P = 0.591), or side (P = 0.574). Supine vs. prone: supine images were rated significantly higher for sharpness, aliasing, and overall image quality. FGT ADCs were significantly higher supine; lesion ADCs were highly correlated (ρc  = 0.92).

DATA CONCLUSION

Based on image quality, supine msDWI outperformed prone msDWI. Lesion ADCs were highly correlated between the two positions, while FGT ADCs were higher in the supine position.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 1.

Arterial spin labeling using spatio-temporal encoding readout for robust perfusion imaging in inhomogenous magnetic fields

PURPOSE

To evaluate the feasibility of spatio-temporal encoding (SPEN) readout for pseudo-continuous ASL (pCASL) in brain, and its robustness to susceptibility artifacts as introduced by aneurysm clips.

METHODS

A 2D self-refocused T₂ *-compensated hybrid SPEN scheme, with super-resolution reconstruction was implemented on a 1.5T Philips system. Q (=BW_chirp *T_chirp ) was varied and, the aneurysm clip-induced artifact was evaluated in phantom (label-images) as well as in vivo (perfusion-weighted signal (PWS)-maps and temporal SNR (tSNR)). In vivo results were compared to gradient-echo EPI (GE-EPI) and spin-echo EPI (SE-EPI). The dependence of tSNR on TR was evaluated separately for SPEN and SE-EPI. SPEN with Q ˜ 75 encodes with the same off-resonance robustness as EPI.

RESULTS

The clip-induced artifact with SPEN decreased with increase in Q, and was smaller compared to SE-EPI and GE-EPI in vivo. tSNR decreased with Q and the tSNR of GE-EPI and SE-EPI corresponded to SPEN with a Q-value of approximately ˜85 and ˜108, respectively. In addition, SPEN perfusion images showed a higher tSNR (p < 0.05) for TR = 4000 ms compared to TR = 2100 ms, while SE-EPI did not. tSNR remained relatively stable when the time between SPEN-excitation and start of the next labeling-module was more than ˜1000 ms.

CONCLUSION

Feasibility of combining SPEN with pCASL imaging was demonstrated, enabling cerebral perfusion measurements with a higher robustness to field inhomogeneity (Q > 75) compared to SE-EPI and GE-EPI. However, the SPEN chirp-pulse saturates incoming blood, thereby reducing pCASL labeling efficiency of the next acquisition for short TRs. Future developments are needed to enable 3D scanning.

Time-dependent diffusivity and kurtosis in phantoms and patients with head and neck cancer

PURPOSE

To assess the reliability of measuring diffusivity, diffusional kurtosis, and cellular-interstitial water exchange time with long diffusion times (100-800 ms) using stimulated-echo DWI.

METHODS

Time-dependent diffusion MRI was tested on two well-established diffusion phantoms and in 5 patients with head and neck cancer. Measurements were conducted using an in-house diffusion-weighted STEAM-EPI pulse sequence with multiple diffusion times at a fixed TE on three scanners. We used the weighted linear least-squares fit method to estimate time-dependent diffusivity,D ( t ) $$ D(t) $$ , and diffusional kurtosis,K ( t ) $$ K(t) $$ . Additionally, the Kärger model was used to estimate cellular-interstitial water exchange time (τ ex $$ {\tau}_{ex} $$ ) fromK ( t ) $$ K(t) $$ .

RESULTS

Diffusivity measured by time-dependent STEAM-EPI measurements and commercial SE-EPI showed comparable results with R2 above 0.98 and overall 5.4 ± 3.0% deviation across diffusion times. Diffusional kurtosis phantom data showed expected patterns: constantD $$ D $$ andK $$ K $$  = 0 for negative controls and slow varyingD $$ D $$ andK $$ K $$ for samples made of nanoscopic vesicles. Time-dependent diffusion MRI in patients with head and neck cancer found that the Kärger model could be considered valid in 72% ± 23% of the voxels in the metastatic lymph nodes. The median cellular-interstitial water exchange time estimated for lesions was between 58.5 ms and 70.6 ms.

CONCLUSIONS

Based on two well-established diffusion phantoms, we found that time-dependent diffusion MRI measurements can provide stable diffusion and kurtosis values over a wide range of diffusion times and across multiple MRI systems. Moreover, estimation of cellular-interstitial water exchange time can be achieved using the Kärger model for the metastatic lymph nodes in patients with head and neck cancer.

Diagnostic Usefulness of Diffusion-Weighted MRI for Axillary Lymph Node Evaluation in Patients with Breast Cancer

This study aimed to determine whether apparent diffusion coefficient (ADC) and morphological features on diffusion-weighted MRI (DW-MRI) can discriminate metastatic axillary lymph nodes (ALNs) from benign in patients with breast cancer. Two radiologists measured ADC, long and short diameters, long-to-short diameter ratio, and cortical thickness and assessed eccentric cortical thickening, loss of fatty hilum, irregular margin, asymmetry in shape or number, and rim sign of ALNs on DW-MRI and categorized them into benign or suspicious ALNs. Pathologic reports were used as a reference standard. Statistical analysis was performed using the Mann-Whitney U test and chi-square test. Overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of DW-MRI were calculated. The ADC of metastatic ALNs was 0.905 × 10^-3 mm²/s, and that of benign ALNs was 0.991 × 10^-3 mm²/s (p = 0.243). All morphologic features showed significant difference between the two groups. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the final categorization on DW-MRI were 77.1%, 93.3%, 79.4%, 92.5%, and 86.2%, respectively. Our results suggest that morphologic evaluation of ALNs on DWI can discriminate metastatic ALNs from benign. The ADC value of metastatic ALNs was lower than that of benign nodes, but the difference was not statistically significant.

Metabolic activity diffusion imaging (MADI): II. Noninvasive, high-resolution human brain mapping of sodium pump flux and cell metrics

We introduce a new ¹ H₂ O magnetic resonance approach: metabolic activity diffusion imaging (MADI). Numerical diffusion-weighted imaging decay simulations characterized by the mean cellular water efflux (unidirectional) rate constant (k_io ), mean cell volume (V), and cell number density (ρ) are produced from Monte Carlo random walks in virtual stochastically sized/shaped cell ensembles. Because of active steady-state trans-membrane water cycling (AWC), k_io reflects the cytolemmal Na⁺ , K⁺ ATPase (NKA) homeostatic cellular metabolic rate (^c MR_NKA ). A digital 3D "library" contains thousands of simulated single diffusion-encoded (SDE) decays. Library entries match well with disparate, animal, and human experimental SDE decays. The V and ρ values are consistent with estimates from pertinent in vitro cytometric and ex vivo histopathological literature: in vivo V and ρ values were previously unavailable. The library allows noniterative pixel-by-pixel experimental SDE decay library matchings that can be used to advantage. They yield proof-of-concept MADI parametric mappings of the awake, resting human brain. These reflect the tissue morphology seen in conventional MRI. While V is larger in gray matter (GM) than in white matter (WM), the reverse is true for ρ. Many brain structures have k_io values too large for current, invasive methods. For example, the median WM k_io is 22s^-1 ; likely reflecting mostly exchange within myelin. The k_io •V product map displays brain tissue ^c MR_NKA variation. The GM activity correlates, quantitatively and qualitatively, with the analogous resting-state brain ¹⁸ FDG-PET tissue glucose consumption rate (^t MR_glucose ) map; but noninvasively, with higher spatial resolution, and no pharmacokinetic requirement. The cortex, thalamus, putamen, and caudate exhibit elevated metabolic activity. MADI accuracy and precision are assessed. The results are contextualized with literature overall homeostatic brain glucose consumption and ATP production/consumption measures. The MADI/PET results suggest different GM and WM metabolic pathways. Preliminary human prostate results are also presented.

Breast MRI during pregnancy and lactation: clinical challenges and technical advances

The breast experiences substantial changes in morphology and function during pregnancy and lactation which affects its imaging properties and may reduce the visibility of a concurrent pathological process. The high incidence of benign gestational-related entities may further add complexity to the clinical and radiological evaluation of the breast during the period. Consequently, pregnancy-associated breast cancer (PABC) is often a delayed diagnosis and carries a poor prognosis. This state-of-the-art pictorial review illustrates how despite currently being underutilized, technical advances and new clinical evidence support the use of unenhanced breast MRI during pregnancy and both unenhanced and dynamic-contrast enhanced (DCE) during lactation, to serve as effective supplementary modalities in the diagnostic work-up of PABC.

Single-shell to multi-shell dMRI transformation using spatial and volumetric multilevel hierarchical reconstruction framework

Single or Multi-shell high angular resolution diffusion imaging (HARDI) has become an important dMRI acquisition technique for studying brain white matter fibers. Existing single-shell HARDI makes it challenging to estimate the intravoxel structure up to the desired resolution. However, multi-shell acquisition (with multiple b-values) can provide higher resolution for the intravoxel structure, which further helps in getting accurate fiber tracts; But, this comes at the cost of larger acquisition time and larger setup. Hence, we propose a novel deep learning architecture for the reconstruction of diffusion MRI volumes for different b-values (degree of diffusion weighting) using acquisitions at a fixed b-value (termed as single-shell) acquisition. This reconstruction has been performed in the spherical harmonics space to better manage varying gradient directions. In this work, we have demonstrated such a reconstruction for b = 3000 s/mm² and b = 2000 s/mm² from b = 1000 s/mm². The proposed Multilevel Hierarchical Spherical Harmonics Coefficients Reconstruction (MHSH) framework takes advantage of contextual information within each slice as well as across the slices by involving Slice Level ReconNet (SLRNet) network and a Volumetric ROI Level ReconNet (VPLRNet) network, respectively. Three-loss functions have been used to optimize network learning, i.e., L₁, Adversarial, and Total Variation Loss. Finally, the network is trained and validated on the publicly available HCP data-set with standard qualitative and quantitative performance measures and achieves promising results.

Differentiation of fibroadenomas versus malignant breast tumors utilizing three-dimensional amide proton transfer weighted magnetic resonance imaging

OBJECTIVE

To explore the value of amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) for differential diagnosis of fibroadenomas and malignant breast tumors.

MATERIALS AND METHODS

This prospective study enrolled 56 patients with suspected breast tumors and performed APTw imaging. Based on the histopathology results, patients were divided into group 1 with malignant breast tumors (n = 41) and group 2 with fibroadenomas (n = 15). The measured image parameters (APTw value, ADC value, type of Time of Intensity Curve, maximum tumor diameter in image) and the maximal diameter of the tumors measured from surgical resection were compared between the two groups, and the diagnostic performance based on these parameters was quantified with ROC curve. Spearman's correlation coefficient was used to analyze the association between APTw or ADC values and ER, PR, HER2, and Ki-67 expressions.

RESULTS

The intraclass correlation coefficients (ICC = 0.87 and 0.91) indicated a good inter-observer agreement of the measured APTw values. APTw values of malignant lesions were significantly higher than those of fibroadenomas (3.21 ± 1.04% vs 1.50 ± 0.54%, p < 0.001). Area under the curve (AUC) obtained from APTw imaging, DWI, DCE, APTw imaging+DWI, APTw imaging+DWI, and APTw imaging+DWI + DCE was 0.959, 0.897, 0.976, 0.997, and 1 respectively. The APTw value showed a negative correlation with ER expression (r = -0.357).

CONCLUSION

APTw imaging yielded similar diagnosis performance in discriminating fibroadenomas and malignant breast tumors when compared to the DCE and better than DWI imaging, and provided supplement information on tumor cell activity to DWI images. The APTw value showed correlations with some prognostic factors for breast cancer.

Diffusivity in breast malignancies analyzed for b > 1000 s/mm2 at 1 mm in-plane resolutions: Insight from Gaussian and non-Gaussian behaviors

Diffusion-weighted imaging (DWI) can improve breast cancer characterizations, but often suffers from low image quality -particularly at informative b > 1000 s/mm² values. The aim of this study was to evaluate multishot approaches characterizing Gaussian and non-Gaussian diffusivities in breast cancer. This was a prospective study, in which 15 subjects, including 13 patients with biopsy-confirmed breast cancers, were enrolled. DWI was acquired at 3 T using echo planar imaging (EPI) with and without zoomed excitations, readout-segmented EPI (RESOLVE), and spatiotemporal encoding (SPEN); dynamic contrast-enhanced (DCE) data were collected using three-dimensional gradient-echo T₁ weighting; anatomies were evaluated with T₂ -weighted two-dimensional turbo spin-echo. Congruence between malignancies delineated by DCE was assessed against high-resolution DWI scans with b-values in the 0-1800 s/mm² range, as well as against apparent diffusion coefficient (ADC) and kurtosis maps. Data were evaluated by independent magnetic resonance scientists with 3-20 years of experience, and radiologists with 6 and 20 years of experience in breast MRI. Malignancies were assessed from ADC and kurtosis maps, using paired t tests after confirming that these values had a Gaussian distribution. Agreements between DWI and DCE datasets were also evaluated using Sorensen-Dice similarity coefficients. Cancerous and normal tissues were clearly separable by ADCs: by SPEN their average values were (1.03 ± 0.17) × 10^-3 and (1.69 ± 0.19) × 10^-3  mm² /s (p < 0.0001); by RESOLVE these values were (1.16 ± 0.16) × 10^-3 and (1.52 ± 0.14) × 10^-3 (p = 0.00026). Kurtosis also distinguished lesions (K = 0.64 ± 0.15) from normal tissues (K = 0.45 ± 0.05), but only when measured by SPEN (p = 0.0008). The best statistical agreement with DCE-highlighted regions arose for SPEN-based DWIs recorded with b = 1800 s/mm² (Sorensen-Dice coefficient = 0.67); DWI data recorded with b = 850 and 1200 s/mm² , led to lower coefficients. Both ADC and kurtosis maps highlighted the breast malignancies, with ADCs providing a more significant separation. The most promising alternative for contrast-free delineations of the cancerous lesions arose from b = 1800 s/mm² DWI. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 3.

Editorial for "Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions"

LEVEL OF EVIDENCE

5 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:608-609.