[Influence of b value on the measurement of contrast and apparent diffusion coefficient in 3.0 Tesla breast magnetic resonance imaging]

Evaluation of apparent diffusion coefficient of two-dimensional BLADE turbo gradient- and spin-echo diffusion-weighted imaging with a breast phantom

This study aimed to evaluate the reliability of apparent diffusion coefficient (ADC) values generated with two-dimensional turbo gradient- and spin-echo with BLADE trajectory diffusion-weighted imaging (TGSE-BLADE-DWI) sequence using a breast diffusion phantom. TGSE-BLADE-DWI and single-shot spin-echo echo-planar imaging (SS-EPI-DWI) were performed using a 3.0 T magnetic resonance imaging scanner. Concordance rates of ADC values and the signal-to-noise ratio (SNR) were compared between TGSE-BLADE-DWI and SS-EPI-DWI. TGSE-BLADE-DWI provided a higher concordance rate for ADC values than SS-EPI-DWI when b-values > 2000s/mm² and a slice thickness of 1 mm were used. TGSE-BLADE-DWI showed less image distortion than SS-EPI-DWI. The SNR of TGSE-BLADE-DWI was higher than that of SS-EPI-DWI, except at a number of excitations of 7 and a slice thickness of 1 mm. In conclusion, TGSE-BLADE-DWI can offer a better SNR, less distortion, and more reliable ADC measurements than SS-EPI-DWI in a breast phantom.

Triexponential Diffusion Analysis of Diffusion-weighted Imaging for Breast Ductal Carcinoma in Situ and Invasive Ductal Carcinoma

Purpose

To obtain detailed information in breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) using triexponential diffusion analysis.

Methods

Diffusion-weighted images (DWI) of the breast were obtained using single-shot diffusion echo-planar imaging with 15 b-values. Mean signal intensities at each b-value were measured in the DCIS and IDC lesions and fitted with the triexponential function based on a two-step approach: slow-restricted diffusion coefficient (D_s) was initially determined using a monoexponential function with b-values > 800 s/mm². The diffusion coefficient of free water at 37°C was assigned to the fast-free diffusion coefficient (D_f). Finally, the perfusion-related diffusion coefficient (D_p) was derived using all the b-values. Furthermore, biexponential analysis was performed to obtain the perfusion-related diffusion coefficient (D^*) and the perfusion-independent diffusion coefficient (D). Monoexponential analysis was performed to obtain the apparent diffusion coefficient (ADC). The sensitivity and specificity of the aforementioned diffusion coefficients for distinguishing between DCIS and IDC were evaluated using the pathological results.

Results

The D_s, D, and ADC of DCIS were significantly higher than those of IDC (P < 0.01 for all). There was no significant correlation between D_p and D_s, but there was a weak correlation between D^* and D. The combination of D_p and D_s showed higher sensitivity and specificity (85.9% and 71.4%, respectively), compared to the combination of D^* and D (81.5% and 33.3%, respectively).

Conclusion

Triexponential analysis can provide detailed diffusion information for breast tumors that can be used to differentiate between DCIS and IDC.

Added value of mean and entropy of apparent diffusion coefficient values for evaluating histologic phenotypes of invasive ductal breast cancer with MR imaging

OBJECTIVES

To study the added value of mean and entropy of apparent diffusion coefficient (ADC) values at standard (800 s/mm²) and high (1500 s/mm²) b-values obtained with diffusion-weighted imaging in identifying histologic phenotypes of invasive ductal breast cancer (IDC) with MR imaging.

METHODS

One hundred thirty-four IDC patients underwent diffusion-weighted imaging with b-values of 800 and 1500 s/mm², and corresponding ADC₈₀₀ and ADC₁₅₀₀ maps were generated. Mean and entropy of volumetric ADC values were compared with molecular markers (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor 2 [HER2], and Ki-67). Associations among morphologic features, ADC metrics, and phenotypes (luminal A, luminal B [HER2 negative], luminal B [HER2 positive], HER2 positive, and triple negative) were evaluated.

RESULTS

Mean ADC values were significantly decreased in ER-positive, PR-positive, and HER2-negative tumors (p < 0.01). Ki-67 ≥ 20% tumors demonstrated significantly higher ADC entropy values compared with Ki-67 < 20% tumors (p < 0.001). Luminal A subtype tended to display lower ADC entropy values compared with other subtypes, while HER2-positive subtype tended to display higher mean ADC values. ADC₁₅₀₀ entropy provided superior diagnostic performance over ADC₈₀₀ entropy (p = 0.04). Independent risk factors were ADC₁₅₀₀ entropy (p = 0.002) associated with luminal A, irregular mass shape (p = 0.018) and ADC₁₅₀₀ entropy (p = 0.022) with luminal B (HER2 positive), mean ADC₁₅₀₀ (p = 0.018) with HER2 positive, and smooth mass margin (p = 0.012) and rim enhancement (p = 0.003) with triple negative.

CONCLUSIONS

Mean and entropy of ADC values provided complementary information and added value for evaluating IDC histologic phenotypes. High-b-value ADC₁₅₀₀ may facilitate better phenotype discrimination.

KEY POINTS

• ADC metrics are associated with molecular marker status in IDC. • ADC ₁₅₀₀ improves differentiation of histologic phenotypes compared with ADC ₈₀₀ . • ADC metrics add value to morphologic features in IDC phenotyping.

How to Improve the Conspicuity of Breast Tumors on Computed High b-value Diffusion-weighted Imaging

PURPOSE

The aim of this study was to compare the tumor conspicuity on actual measured diffusion-weighted images (aDWIs) and computed DWI (cDWI) of human breast tumors and to examine, by use of a phantom, whether cDWI improves their conspicuity.

MATERIALS AND METHODS

We acquired DWIs (b-value 0, 700, 1400, 2100, 2800, and 3500 s/mm²) of 148 women with breast tumors. cDWIs with b-values of 1400, 2100, 2800, and 3500 s/mm² were calculated from aDWI scans where b = 0 and 700 s/mm²; the tumor signal-to-noise ratio (SNR) was compared at each b-value. We also subjected a phantom harboring a breast tumor and mammary glands to DWI. For reference we used two models. The model with b = 0, 1000, 1500, 2000, 2500, and 3000 s/mm² was our multiple b-value model. In the single b-value model, we applied b = 0 and 1000 s/mm² and changed the number of excitations (NEX). cDWIs were generated at b = 0 and 1000 and used to compare the SNR, the contrast ratio (CR), and the contrast-to-noise ratio (CNR).

RESULTS

In the phantom study, the CNR of cDWI generated from high SNR images obtained at lower b-values and a high NEX was outperformed aDWI. However, the CR and CNR on cDWI obtained using the same scanning parameters were inferior to aDWI scans. Similarly, in the clinical study, breast tumor conspicuity was worse on high b-value cDWIs than aDWIs.

CONCLUSION

To improve tumor conspicuity on cDWI, the quality of the source images must be improved. It may easily cause inferior conspicuity to aDWIs if high b-value cDWIs were generated from insufficient SNR images.

Apparent diffusion coefficient value in invasive ductal carcinoma at 3.0 Tesla: is it correlated with prognostic factors?

OBJECTIVE

To investigate the correlation between apparent diffusion coefficient (ADC) values and prognostic factors in patients with invasive ductal carcinoma (IDC).

METHODS

48 lesions belonging to 47 patients with histopathologically proven IDC were examined using conventional MR and diffusion-weighted imaging at a 3.0-T system. All of the patients had modified radical mastectomies or breast-sparing surgery plus axillary lymph node dissection. The ADC values acquired from the ADC maps consisted of six different b-values (0, 50, 100, 500, 1000 and 1500 s mm(-2)) and were compared with the patients' ages, tumour size, histological grade of the lesions, tumour localization, lesions' distance to skin surface and nipples, the existence of axillary lymph node involvement, the number of involved axillary lymph nodes, oestrogen/progesterone receptor status, peritumoral lymphovascular invasion status and the existence of human epidermal growth factor 2 (c-erbB-2) overexpression.

RESULTS

A statistically significant relationship was found regarding axillary lymph node involvement (p = 0.027), and oestrogen/progesterone receptor status (p = 0.013). No significant relationship was detected regarding other prognostic factors (p > 0.05).

CONCLUSION

Among various prognostic factors, ADC values were significantly correlated with only axillary lymph node positivity and oestrogen/progesterone receptor status.

ADVANCES IN KNOWLEDGE

In the present study, the relationship between ADC values of IDC lesions that are acquired at a high magnetic field (3.0 T) system by using multiple b-values and some specific prognostic factors that were not evaluated before in the medical literature was investigated.

Diffusion weighted imaging and apparent diffusion coefficient in 3 tesla magnetic resonance imaging of breast lesions

OBJECTIVE

To evaluate the utility of diffusion-weighted-imaging (DWI) and apparent-diffusion-coefficient (ADC) in a 3T magnetic-resonance-imaging (MRI) study of breast cancer. In particular, the study aims to classify ADC-values according to histology either for benign or malignant lesions.

METHODS

110 Breast MRI with MRI-DWI sequences and quantitative evaluation of the ADC were retrospectively reviewed. Results obtained with MRI-DWI and with biopsy were analyzed and ADC values were compared to histological results.

RESULTS

MRI showed a 95.5% sensitivity and a 83.7% specificity. The mean ADC values of benign and malignant lesions were 2.06 ± 0.19 and 1.03 ± 0.07 mm(2)/s, respectively (p < .05).

CONCLUSIONS

DWI and ADC-values could help distinguishing malignant and benign breast masses.

Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience

PURPOSE

The aim of this work was to perform a qualitative and quantitative comparison of the performance of two fat suppression techniques on breast diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

Fifty-one women underwent clinical breast magnetic resonance imaging, including DWI with short TI inversion recovery (STIR) and spectral attenuated inversion recovery (SPAIR). Four were excluded from the analysis due to image artefacts. Rating of fat suppression uniformity and lesion visibility were performed. Agreement between the two sequences was evaluated. Additionally, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values for normal gland, benign and malignant lesions were compared. Receiver operating characteristic analysis was also performed.

RESULTS

From the 52 lesions found, 47 were detected by both sequences. DWI-STIR evidenced more homogeneous fat suppression (p = 0.03). Although these lesions were seen with both techniques, DWI-SPAIR evidenced higher score for lesion visibility in nine of them. SNR and CNR were comparable, except for SNR in benign lesions (p < 0.01), which was higher for DWI-SPAIR. Mean ADC values for lesions were similar. ADC for normal fibroglandular tissue was higher when using DWI-STIR (p = 0.006). Sensitivity, specificity, accuracy and area under the curve values were alike: 84.0 % for both; 77.3, 71.4 %; 80.9, 78.3 %; 82.5, 81.3 % for DWI-SPAIR and DWI-STIR, respectively.

CONCLUSION

DWI-STIR showed superior fat suppression homogeneity. No differences were found for SNR and CNR, except for SNR in benign lesions. ADCs for lesions were comparable. Findings in this study are consistent with previous studies at 1.5 T, meaning that both fat suppression techniques are appropriate for breast DWI at 3.0 T.

Investigation of the optimal b-value to detect breast tumors with diffusion weighted imaging by 1.5-T MRI

Background

Previous studies have reported that the signal attenuation of diffusion-weighted magnetic resonance imaging (DWI) for normal breast tissue and tumor were well fitted by a monoexponential and a biexponential function, respectively. The aim of this study was to investigate the optimal b-value to detect breast tumors from DWI signal attenuations.

Methods

Sixty-four subjects with breast cancer underwent DWI using six b-values up to 3500 s/mm². The signal attenuations of normal breast and tumor were fitted by mono- and biexponential functions, respectively. The maximum contrast b-values were estimated and compared in terms of frequency.

Results

In almost all cases, the contrast increased with a b-value from 0 to approximately 1500 s/mm². For b > 1500 s/mm², the contrast decreased. The highest contrast b-value in the range of 0 to 2500 s/mm² most frequently was b = 1500 and the next most frequent was 1400 s/mm². Comparing sensitivity and specificity between b = 700 and b = 1400 s/mm², b =1400 s/mm² was slightly superior.

Conclusion

Based on these results, DWI with a b-value of approximately 1400-1500 s/mm² is recommended for optimizing breast tumor detectability.

Optimization of the parameters for diffusion tensor magnetic resonance imaging data acquisition for breast fiber tractography at 1.5 T

INTRODUCTION

Diffusion tensor MRI has emerged as a promising tool for the analysis of the microscopic properties of tissues. Optimizing image acquisition parameters is essential for producing high-quality DTI. This study aimed to optimize the parameters for DTI data acquisition for breast fiber tractography at 1.5 T.

PATIENTS AND METHODS

A total of 21 healthy volunteers received breast DTI scanning using an ASSET-based EPI technique operated under different parameters including b value, the number of diffusion gradient directions, and spatial resolution. The images were analyzed for signal-to-noise, signal intensity ratio, mean number and length of reconstructive fiber tracts, and fractional anisotropy value.

RESULTS

The optimal acquisition parameters at 1.5 T for breast DT-MRI fiber tractography were determined as follows: axial 31 direction, b = 600 seconds per mm(2), matrix 128 × 128 with slice thickness of 3 mm.

CONCLUSION

The optimization of data acquisition parameters could improve the quality of breast DT-MRI images and assist fiber tractography at 1.5 T.