Combination of chemical suppression techniques for dual suppression of fat and silicone at diffusion-weighted MR imaging in women with breast implants

Technical Advancements in Abdominal Diffusion-weighted Imaging

Since its first observation in the 18th century, the diffusion phenomenon has been actively studied by many researchers. Diffusion-weighted imaging (DWI) is a technique to probe the diffusion of water molecules and create a MR image with contrast based on the local diffusion properties. The DWI pixel intensity is modulated by the hindrance the diffusing water molecules experience. This hindrance is caused by structures in the tissue and reflects the state of the tissue. This characteristic makes DWI a unique and effective tool to gain more insight into the tissue's pathophysiological condition. In the past decades, DWI has made dramatic technical progress, leading to greater acceptance in clinical practice. In the abdominal region, however, acquiring DWI with good quality is challenging because of several reasons, such as large imaging volume, respiratory and other types of motion, and difficulty in achieving homogeneous fat suppression. In this review, we discuss technical advancements from the past decades that help mitigate these problems common in abdominal imaging. We describe the use of scan acceleration techniques such as parallel imaging and compressed sensing to reduce image distortion in echo planar imaging. Then we compare techniques developed to mitigate issues due to respiratory motion, such as free-breathing, respiratory-triggering, and navigator-based approaches. Commonly used fat suppression techniques are also introduced, and their effectiveness is discussed. Additionally, the influence of the abovementioned techniques on image quality is demonstrated. Finally, we discuss the current and future clinical applications of abdominal DWI, such as whole-body DWI, simultaneous multiple-slice excitation, intravoxel incoherent motion, and the use of artificial intelligence. Abdominal DWI has the potential to develop further in the future, thanks to scan acceleration and image quality improvement driven by technological advancements. The accumulation of clinical proof will further drive clinical acceptance.

Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives

For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology.

KEY POINTS

• Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.

[Evaluation of Fat Suppression of Diffusion-weighted Imaging Using Section Select Gradient Reversal Technique on 3 T Breast MRI]

This study evaluates fat suppression of diffusion-weighted imaging (DWI) using section select gradient reversal (SSGR) technique in clinical images on 3 T breast MRI. A total of 20 patients with breast cancer were examined at a Philips Ingenia 3 T MRI. We acquired DWI with SPAIR, SSGR-SPAIR, STIR, and SSGR-STIR. We evaluated contrast between the fat region and lesion, the coefficient of variance (CV) of the fat region and the apparent diffusion coefficient (ADC) of normal breast tissue and lesion. The contrast between the fat region and lesion was improved with SSGR technique. The CV of the fattest region did not have any significant difference in SPAIR technique (p>0.05), but it was significantly decreased in the STIR technique using SSGR technique (p<0.05). Positive correlation was observed in ADC value between SPAIR and other fat suppression techniques (SSGR-SPAIR, STIR, SSGR-STIR). DWI using SSGR technique was suggested to be effective on 3 T breast MRI.

Removing silicone artifacts in diffusion-weighted breast MRI by means of shift-resolved spatiotemporally encoding

PURPOSE

Evaluate the usefulness of diffusion-weighted spatiotemporally encoded (SPEN) methods to obtain apparent diffusion coefficient (ADC) maps of fibroglandular human breast tissue, in the presence of silicone implants.

METHODS

Seven healthy volunteers with breast augmentation were scanned at 3 Tesla (T) using customized SPEN sequences yielding separate silicone and water (1) H images in one scan, together with their corresponding diffusion-weightings.

RESULTS

SPEN's ability to deliver multiple spectrally resolved images in a single scan, coupled to the method's substantial robustness to magnetic field heterogeneities, served to acquire ADC maps that could be freed from contributions that did not belong to fibroglandular tissue.

CONCLUSION

SPEN-based sequences incorporating spectral discrimination and diffusion-weighting enable the acquisition of reliable ADC maps despite the presence of dominant signals from silicone implants, thereby opening new screening possibilities for the identification of malignancies in breast augmented patients.

3-T breast diffusion-weighted MRI by echo-planar imaging with spectral spatial excitation or with additional spectral inversion recovery: an in vivo comparison of image quality

OBJECTIVE

To compare conventional diffusion-weighted imaging (DWI) with spectral spatial excitation (cDWI) and an enhanced DWI with additional adiabatic spectral inversion recovery (eDWI) for 3-T breast magnetic resonance imaging (MRI).

METHODS

Twenty-four patients were enrolled in the study with both cDWI and eDWI. Three breast radiologists scored cDWI and eDWI images of each patient for fat-suppression quality, geometric distortion, visibility of normal structure and biopsy-proven lesions, and overall image quality. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) for evaluable tissues were measured. Statistical tests were performed for qualitative and quantitative comparisons.

RESULTS

Diffusion-weighted imaging with spectral spatial excitation yielded significantly higher CNR and SNR on a lesion basis, and higher glandular CNR and SNR and muscle SNR on a patient basis. Enhanced DWI also yielded significantly higher qualitative scores in all categories. No significant difference was found in ADC values.

CONCLUSIONS

Enhanced DWI provided superior image quality and higher CNR and SNR on a lesion basis. Enhanced DWI can replace cDWI for 3-T breast DWI.

Correlation between 3T apparent diffusion coefficient values and grading of invasive breast carcinoma

PURPOSE

The aim of this study was to evaluate whether the apparent diffusion coefficient (ADC) provided by 3.0T (3T) magnetic resonance diffusion-weighted imaging (DWI) varied according to the grading of invasive breast carcinoma.

MATERIALS AND METHODS

A total of 92 patients with 96 invasive breast cancer lesions were enrolled; all had undergone 3T magnetic resonance imaging (MRI) for local staging. All lesions were confirmed by histological analysis, and tumor grade was established according to the Nottingham Grading System (NGS). MRI included both dynamic contrast-enhanced and DWI sequences, and ADC value was calculated for each lesion. ADC values were compared with NGS classification using the Mann-Whitney U and the Kruskal-Wallis H tests. Grading was considered as a comprehensive prognostic factor, and Rho Spearman test was performed to determine correlation between grading and tumor size, hormonal receptor status, HER2 expression and Ki67 index. Pearson's Chi square test was carried out to compare grading with the other prognostic factors.

RESULTS

ADC values were significantly higher in G1 than in G3 tumors. No significant difference was observed when G1 and G3 were compared with G2. Tumor size, hormonal receptor status, HER2 expression and Ki67 index correlated significantly with grading but there was a significant difference only between G1 and G3 related to the ER and PR status, HER2 expression and Ki67 index. There was no statistically significant difference in lesion size between the two groups.

CONCLUSION

ADC values obtained on 3T DWI correlated with low-grade (G1) and high-grade (G3) invasive breast carcinoma. 3T ADC may be a helpful tool for identifying high-grade invasive breast carcinoma.

Diffusion-weighted imaging: determination of the best pair of b-values to discriminate breast lesions

OBJECTIVE

In breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0 T.

METHODS

152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000 s mm(-2). ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types.

RESULTS

Considering the cut-off values 1.46 and 1.49 × 10(3)mm(2) s(-1), the pairs 50, 1000 and 200, 800 s mm(-2) showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000 s mm(-2) with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86 ± 0.46, 1.77 ± 0.37 and 1.15 ± 0.46 × 10(-3) mm(2) s(-1) for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCall (ADC calculated from the full set of b - values) [difference = 0.0075 × 10(-3) mm(2) s(-1); confidence interval 95%: (-0.0036; 0.0186); p = 0.18].

CONCLUSION

The diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000 s mm(-2).

ADVANCES IN KNOWLEDGE

The best b-value pair for lesion discrimination and characterization through ADC quantification was 50, 1000 s mm(-2).

Dual-energy CT for the evaluation of silicone breast implants

OBJECTIVE

The evaluation of breast implants for rupture is currently the domain of ultrasound and MRI, while mammography is of very limited diagnostic value. Recently, specific visualisation of silicone has become feasible using dual-energy CT. Our objective was to evaluate whether it is feasible to identify silicone in breast implants by dual-energy CT and to reliably diagnose or rule out ruptures.

METHODS

Seven silicone breast implant specimens were examined on dual-source CT at 100- and 140-kV tube potential with a 0.8-mm tin filter (collimation 128 × 0.6 mm, current-time products 165 and 140 mAsref with modulation, rotation time 0.28 s, pitch 0.55). Two patients scheduled for implant removal or replacement were examined with identical parameters.

RESULTS

The silicone of the implant specimens showed a strong dual-energy signal. In one patient, both implants were intact, while a rupture was identified in the other patient. Ultrasound, MRI, surgical findings and histology confirmed the dual-energy CT diagnosis.

CONCLUSION

Dual-energy CT may serve as an alternative technique for speedy evaluation of silicone breast implants. Specific clinical studies are required to determine the diagnostic accuracy and define indications for this technique.